CN112750512A

CN112750512A - Data processing method, client, server, system and storage medium

Info

Publication number: CN112750512A
Application number: CN201911051307.3A
Authority: CN
Inventors: 张明耀
Original assignee: Alibaba Group Holding Ltd
Current assignee: Alibaba Group Holding Ltd
Priority date: 2019-10-31
Filing date: 2019-10-31
Publication date: 2021-05-04

Abstract

The embodiment of the application provides a data processing method, a client, a server, a system and a storage medium. In the data processing system, based on interaction between the client and the server, when a first user initiates an operation of checking health data of a second user, basic health data contained in target health data can be displayed in a classified mode, and health analysis results contained in the target health data can be displayed in a classified mode, so that multi-dimensional and multi-angle flexible display of the health data is achieved, the first user can be assisted to know the health state of the second user quickly, and data query efficiency is improved.

Description

Data processing method, client, server, system and storage medium

Technical Field

The present application relates to the field of health informatization technologies, and in particular, to a data processing method, a client, a server, a system, and a storage medium.

Background

For doctors, when diagnosing the disease condition of a patient, the historical disease condition and the historical diagnosis and treatment mode of the patient are often used as reference bases for current diagnosis. However, most patients often cannot effectively remember or describe their previous illness and diagnosis and treatment modes before visiting the doctor. Therefore, a new solution is yet to be proposed.

Disclosure of Invention

Various aspects of the present application provide a data processing method, a client, a server, a system, and a storage medium, which implement multidimensional, multi-angle flexible display of health data, and are beneficial to assist a first user to quickly know the health status of a second user, thereby improving data query efficiency.

The embodiment of the application provides a data processing method, which is suitable for a client and comprises the following steps: responding to the operation of inquiring the health data of a second user by a first user, and acquiring target health data of the second user from a server; displaying at least one basic information display area and at least one analysis result display area on a first page; in the at least one basic information display area, basic health data in the target health data are displayed in a classified mode, and in the at least one analysis result display area, health analysis results in the target health data are displayed in a classified mode.

An embodiment of the present application further provides a data processing method, which is applicable to a server, and includes: receiving a data acquisition request, wherein the data acquisition request is sent by a client when a first user inquires health data of a second user; acquiring basic health data and health analysis results in the health data of the second user according to the data acquisition request, and taking the basic health data and the health analysis results as target health data; and sending the target health data to the client for display.

An embodiment of the present application further provides a data processing method, which is applicable to a server, and includes: receiving a data acquisition request, wherein the data acquisition request is sent by a client when a first user inquires health data of a second user, and the data acquisition request carries identity information of the first user; if the first user is identified as a medical subsidy processing user according to the identity information of the first user, acquiring diagnosis and treatment records and diagnosis and treatment expense data corresponding to the target disease type meeting the medical subsidy condition from the health data of the second user; and sending the diagnosis and treatment records and the diagnosis and treatment expense data corresponding to the target disease type to a client for displaying so as to be checked by the first user.

An embodiment of the present application further provides a data processing method, which is applicable to a server, and includes: receiving a data acquisition request, wherein the data acquisition request is sent by a client when a first user inquires health data of a second user, and the data acquisition request carries identity information of the first user; if the first user is identified as a commercial insurance processing user according to the identity information of the first user, sending an authorization request to the second user according to the identity information of the first user; if receiving an authorization notification message returned by the second user according to the authorization request, acquiring health data associated with commercial insurance from the health data of the second user; and sending the health data associated with the commercial insurance to a client for displaying so as to be viewed by the first user.

An embodiment of the present application further provides a data processing method, including: receiving a data acquisition request, wherein the data acquisition request is sent by a client when a first user inquires health data, and the data acquisition request carries identity information of the first user; if the first user is identified as a disease control user in a set geographical range according to the identity information of the first user, acquiring medical data of a plurality of medical institutions in the set geographical range; calculating the disease distribution characteristics in the set region range according to the medical data; and sending the disease distribution characteristics to a client for displaying so as to be viewed by the first user.

An embodiment of the present application further provides a health data display device, including: the acquisition module is used for responding to the operation of inquiring the health data of a second user by a first user and acquiring the target health data of the second user from a server; the display module is used for displaying at least one basic information display area and at least one analysis result display area on a first page; in the at least one basic information display area, basic health data in the target health data are displayed in a classified mode, and in the at least one analysis result display area, health analysis results in the target health data are displayed in a classified mode.

An embodiment of the present application further provides a health data display device, including: the system comprises a receiving module, a sending module and a receiving module, wherein the receiving module is used for receiving a data acquisition request, and the data acquisition request is sent by a client when a first user inquires health data of a second user; the data acquisition module is used for acquiring basic health data and health analysis results in the health data of the second user according to the data acquisition request, and the basic health data and the health analysis results are used as target health data; and the sending module is used for sending the target health data to the client for displaying.

An embodiment of the present application further provides a client, including: a memory, a processor, and a communications component; the memory is to store one or more computer instructions; the processor is to execute the one or more computer instructions to: and executing the steps in the data processing method provided by the embodiment of the application.

An embodiment of the present application further provides a server, including: a memory, a processor, and a communications component; the memory is to store one or more computer instructions; the processor is to execute the one or more computer instructions to: the steps in the data processing method provided by the embodiment of the application are executed.

The embodiments of the present application further provide a computer-readable storage medium storing a computer program, where the computer program can implement the steps in the data processing method provided in the embodiments of the present application when executed.

An embodiment of the present application further provides a data processing system, including: a client and a server; wherein the client is configured to: according to the operation of a first user for inquiring the health data of a second user, acquiring target health data of the second user from the server, displaying basic health data in the target health data in a classified mode, and displaying health analysis results in the target health data in a classified mode; the server is configured to: and when the data acquisition request is received, acquiring basic health data and health analysis results in the health data of the second user as target health data, and sending the target health data to the client.

In the data processing system provided by the embodiment of the application, based on interaction between the client and the server, when the first user initiates an operation of checking health data of the second user, basic health data contained in the target health data can be displayed in a classified mode, and health analysis results contained in the target health data can be displayed in a classified mode, so that multi-dimensional and multi-angle flexible display of the health data is achieved, the first user can be assisted to know the health state of the second user quickly, and the data query efficiency is improved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:

FIG. 1a is a block diagram of a data processing system according to an exemplary embodiment of the present application;

FIG. 1b is a diagram illustrating an example embodiment of the present application for obtaining code vectors of departments;

FIG. 1c is a schematic diagram of obtaining target health data according to coding vectors of departments according to an exemplary embodiment of the present application;

FIG. 2a is a schematic illustration of a client page provided by an exemplary embodiment of the present application;

FIG. 2b is an illustration of a client page provided in another example embodiment of the present application;

FIG. 3a is an illustration of a detail data presentation page provided in an exemplary embodiment of the present application;

FIG. 3b is an illustration of a detail data presentation page provided in another exemplary embodiment of the present application;

FIG. 3c is an illustration of a detail data presentation page provided in accordance with yet another exemplary embodiment of the present application;

FIG. 4 is a schematic flow chart diagram illustrating a data processing method according to another exemplary embodiment of the present application;

FIG. 5a is a schematic flow chart diagram illustrating a data processing method according to another exemplary embodiment of the present application;

FIG. 5b is a schematic flow chart diagram illustrating a data processing method according to another exemplary embodiment of the present application;

FIG. 5c is a schematic flow chart diagram illustrating a data processing method according to another exemplary embodiment of the present application;

FIG. 5d is a schematic flow chart diagram illustrating a data processing method according to another exemplary embodiment of the present application;

FIG. 6 is a schematic diagram of a health data display device according to an exemplary embodiment of the present application;

FIG. 7 is a schematic diagram of a health data display apparatus according to another exemplary embodiment of the present application;

fig. 8 is a schematic structural diagram of a client according to an exemplary embodiment of the present application;

fig. 9 is a schematic structural diagram of a server according to an exemplary embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

In order to overcome the defect that in the prior art, when a patient goes to a doctor, the patient cannot accurately provide his or her previous illness state and diagnosis and treatment mode to provide a reference for the current doctor, in some embodiments of the present application, a solution is provided.

Fig. 1a is a schematic structural diagram of a data processing system according to an exemplary embodiment of the present application, and as shown in fig. 1a, the data processing system 100 includes: a client 10 and a server 20.

In the present embodiment, the client 10 refers to a device capable of providing a health data query operation to a first user and having a communication function. The implementation of the client 10 may be different in different application scenarios. For example, in some scenarios, the client 10 may appear as a user-side cell phone, tablet, computer device, or the like. The first user may initiate a query operation for the health data through a plug-in, an application, or a browser provided by the client 10 as described above.

In some embodiments, the client 10 may include a touch screen through which a first user may initiate a query operation for health data. Of course, in other embodiments, the client 10 may include a physical button, an external keyboard, a mouse, or a voice input device for facilitating the first user to initiate the health data query operation, which is not described herein.

The server 20 refers to a device capable of providing a health data management function, a health data access function, a health data analysis calculation function, and a communication function. In some embodiments, the server 20 may be implemented as a conventional server, a cloud host, a virtual center, or the like, which is not limited in this embodiment. The server device mainly includes a processor, a hard disk, a memory, a system bus, and the like, and is similar to a general computer architecture, and is not described in detail.

In the data processing system 100, the client 10 may send a corresponding data acquisition request to the server 20 to request the server 20 to provide the second user's health data according to an operation of querying the second user's health data by the first user. When receiving the data acquisition request sent by the client 10, the server 20 may acquire the basic health data and the health analysis result in the health data of the second user as the target health data, and send the target health data to the client 10. When the client 10 receives the target health data of the second user returned by the server 20, the basic health data in the target health data can be displayed in a classified manner, and the health analysis result in the target health data can be displayed in a classified manner for the first user to view.

The health data of the second user includes various data for describing the health status of the second user, and the health data includes raw data directly generated by the data source and also includes result data obtained by processing and analyzing the raw data provided by the data source, which is not limited in this embodiment.

For convenience of description, in this embodiment, the original data directly generated by the data source is described as the basic health data, and the result data obtained by processing and analyzing the original data is described as the health analysis result.

The health analysis result is used for performing macro description on the overall health state of the second user or performing key description on certain health problems, so that the first user can quickly know the health state of the second user.

The basic health data may include medical data such as a case, a medical record, and a medical record generated when the second user visits a medical institution, may also include a physical examination report of the second user during a physical examination of the medical institution or the physical examination institution, and may also include other data that affect the health status, such as a living environment, a working environment, a dietary habit, sleep data, and exercise data of the second user, which is not limited in this embodiment.

Wherein, the medical data such as case, case history, medical record that the second user produced when medical institution visits the doctor includes: medical data generated when a second user diagnoses in medical institutions belonging to different regions; and/or medical data generated by the second user while performing a medical procedure in a department affiliated with a different medical institution. That is, medical data generated by different hospitals of different places of the second user may be shared, and medical data generated by different departments may also be shared. Furthermore, the coverage scope of the health data of the second user can be greatly enriched, and the comprehensive summary of the health data of the second user is facilitated. In some scenarios, the comprehensive health data obtained by the summary is convenient for different doctors to perform consultation aiming at certain diseases of the user, and is not repeated.

In the data processing system 100, to implement the above-mentioned interaction process between the client 10 and the server 20, the client 10 and the server 20 may establish a communication connection, and a specific communication connection manner may depend on an actual application scenario.

In some exemplary embodiments, the client 10 and the server 20 may communicate with each other wirelessly using wired communication. The WIreless communication mode includes short-distance communication modes such as bluetooth, ZigBee, infrared, WiFi (WIreless-Fidelity), long-distance WIreless communication modes such as LORA, and WIreless communication mode based on a mobile network. When the mobile network is connected through communication, the network format of the mobile network may be any one of 2G (gsm), 2.5G (gprs), 3G (WCDMA, TD-SCDMA, CDMA2000, UTMS), 4G (LTE), 4G + (LTE +), 5G, WiMax, and the like.

In this embodiment, based on the interaction between the client 10 and the server 20, when the first user initiates an operation of viewing the health data of the second user, the basic health data included in the target health data can be displayed in a classified manner, and the health analysis result included in the target health data can be displayed in a classified manner, so that the multi-dimensional and multi-angle flexible display of the health data is realized, the first user is facilitated to quickly know the health state of the second user, and the data query efficiency is improved.

In the above and following embodiments of the present application, the first user and the second user may be different users or the same user, and the present embodiment is not limited. Under different application scenarios, the first user and the second user can be implemented in different roles.

For example, in some scenarios, a first user may be implemented as a medical person of a medical facility, such as a doctor, nurse, or the like, and a second user may be implemented as a visiting patient. Doctors can assist patients in disease diagnosis and treatment by inquiring health data of the patients.

In other scenarios, the first user and the second user may be implemented as the same user, and the user may learn about the health status of the user by querying the health data of the user.

In still other scenarios, the first user may be implemented as a guardian of the second user, who may learn about the health condition of the person being guarded by querying the health data of the person being guarded.

In the following embodiments, the data processing system 100 provided in the embodiments of the present application will be further described by taking the first user as a doctor and the second user as a patient.

In the foregoing and following embodiments of the present application, optionally, when managing the health data of the second user, the server 20 may perform data mining and analysis on the health data of the second user, and add a data tag to the health data according to a result of the data mining and analysis, where for convenience of description, the data tag corresponding to the health data is marked as the first data tag.

In some embodiments, the first data tag may be a category tag that categorizes the health data. For example, data corresponding to different diseases in the health data may be tagged with a disease. For example, a cold label may be marked on the medical data generated when the second user sees a cold, a gastroenteritis label may be marked on the medical data generated when the second user sees a gastroenteritis, and a coronary heart disease label may be marked on the medical data generated when the second user sees a coronary heart disease. For example, department labels may be marked on data corresponding to diseases belonging to different departments in the health data, for example, a dermatology label may be marked on medical data generated when the second user visits skin diseases, and an ophthalmic label may be marked on medical data generated when the second user visits cataracts. For another example, each disease may be labeled with a disease group to which the disease belongs in the medical field. For example, a respiratory disease label can be marked on a cold label, a digestive disease label can be marked on a gastroenteritis label, and a circulatory disease label can be marked on coronary heart disease, which are not described in detail.

In other embodiments, the first data tag may be a data tag obtained by classifying the data included in each case. For example, for a case, the data related to the assay may be labeled with the assay tag, the data related to the examination may be labeled with the examination tag, the data related to the operation may be labeled with the operation tag, and the data related to the diagnosed disease type may be labeled with the disease type tag, which will not be described in detail.

Based on this, the server 20 may obtain a tag of the data requested to be queried by the first user when receiving the data obtaining request corresponding to the first user, which is described as a second data tag below. Then, at least one data label matched with the second data label in the first data label is inquired, and the health data corresponding to the at least one data label is used as the target health data.

For example, if the first user requests to query the cold data of the second user, the server 20 obtains a cold tag or a respiratory disease tag corresponding to the cold data. Next, the server 20 may obtain, from the health data of the second user, a part of the medical data that fits the cold tag or the respiratory illness tag as the target health data.

In the foregoing embodiments, a technical solution is described in which the server 20 may obtain the basic health data included in the target health data according to the data obtaining request sent by the client 10, and in some embodiments, the obtained basic health data conforms to the query intention of the first user. The query intention of the first user is used for screening out partial data from the large amount of health data so as to meet the query requirement of the first user. The screened partial data may include health data that the first user is interested in, health data that the first user pays attention to, or health data that meets the actual business requirement of the first user, which is not limited in the embodiment of the present application.

In this embodiment, when the server 20 receives the data acquisition request sent by the client 10, the query intention of the first user may be estimated. It should be understood that the estimation of the query intention of the first user refers to the estimation of the query intention of the first user in advance when the first user does not provide the query purpose, and further, under the condition that the first user does not sense, data which may meet the query requirement of the first user can be actively recommended to the first user.

Server 20 may be implemented in conjunction with at least one of the intent description data in predicting the first user's query intent. The intention description data may include any data capable of reflecting the query intention of the first user, and this embodiment is not limited.

In some embodiments, the at least one intent description data may include: first intent description data associated with a first user and/or second intent description data associated with a second user. In different application scenarios, the implementation contents of the first intention description data and the second intention description data are different, and this embodiment does not limit this. Embodiments of acquiring the first intention description data and the second intention description data will be exemplified below.

In some exemplary embodiments, when a first user initiates an operation to the client 10 to query the second user for wellness data, identification information of the second user may be entered. Alternatively, when the client 10 sends a data acquisition request to the server 20, the identification of the first user and the identification of the second user may be added to the data acquisition request. The identification mark may be an account number, an identity number, a name, or other identity marks, or may also be a fingerprint, an iris, or a facial image biometric mark, which is not limited in this embodiment.

Based on the above, after receiving the data obtaining request, the server 20 may obtain the first intention description data associated with the first user according to the identification of the first user carried in the data obtaining request, and/or obtain the second intention description data associated with the second user according to the identification of the second user carried in the data obtaining request.

In some embodiments, optionally, the first intent description data may include: at least one of attribute information of the first user, historical query behavior and preset query conditions.

Optionally, the attribute information may include: at least one of affiliated medical institutions, affiliated departments, areas of excellence, directions of indications, and historical diagnosis and treatment records. When the first user is implemented as a doctor, the attribute information of the first user can reflect which health data of the patient is required as assistance when the first user actually performs a disease diagnosis service. For example, when a doctor is affiliated with maxillofacial surgery of an oral hospital and specializes in the field of deformed teeth correction, the inquiry intention of the doctor may be considered to be associated with oral health data of a patient.

In some exemplary embodiments, the attribute information of the first user is carried by the data acquisition request sent by the client 10. When the server 20 receives the data obtaining request, it may parse the data obtaining request to obtain the attribute information of the first user.

In other exemplary embodiments, the attribute information of the first user and its correspondence with the identification of the first user is stored at the server 20. After obtaining the identification of the first user from the data obtaining request, the server 20 may obtain the attribute information of the first user based on the correspondence.

Optionally, the historical query behavior of the first user may include: and the first user inquires at least one of inquiry sequence, inquiry frequency and input inquiry keywords when inquiring different health data in a historical time period. When the first user is implemented as a doctor, the historical query behavior of the first user may reflect the query habits and the attention level to different health data. Based on the degree of attention, the current query intent of the physician can be estimated.

Optionally, the query condition preset by the first user may be a query condition preset by the first user before querying the health data of the second user, and the query condition may include: and at least one of a query time period, a query keyword, a data category and a data tag corresponding to the data.

In some embodiments, optionally, the second intent description data may include: at least one of a historical visit department of the second user, a distribution characteristic of the health data of the second user, a generation time of the different health data, and a frequency of queries of the different health data.

Optionally, the historical visiting department of the second user refers to a visiting department that the second user visits within a set historical time period or all visiting departments that the second user visits in the past. Each time the second user goes to a department for a medical treatment, health data corresponding to the department can be generated, such as a disease diagnosis result, a medication prescription, an operation condition, a test condition and the like generated by the medical treatment. The departments visited by the user before can reflect the past medical history of the user, and the past medical history has certain influence on the current diseases visited by the user or the departments visited by the user before, so that the query intention of the first user can be estimated through the departments visited by the second user before.

Optionally, the distribution characteristic of the health data of the second user may be represented by a data amount of the medical data corresponding to different disease types in the health data of the second user. If the data volume of the medical data corresponding to one or more disease types is large, it can be considered that the disease type has a large influence on the health of the second user. Therefore, the distribution characteristics of the health data of the second user are used as the intention description data, which is beneficial to prompting the first user to focus on the medical data corresponding to the disease type.

Optionally, the generation time of the different health data of the second user may reflect the dynamic change of the health data of the second user. It should be appreciated that the health data of the second user in the time period closer to the current time is more beneficial to assist in analyzing the current health condition of the second user. Therefore, the generation time of the different health data of the second user is used as the intention description data, which is beneficial to prompting the first user to pay attention to the health data of the second user in the time period closer to the current time.

Optionally, the query frequency of the different health data of the second user may reflect which data of the different health data of the second user may make more contribution to the auxiliary analysis of the health condition of the second user. Therefore, the frequency of querying different health data is used as the intention description data, which is beneficial for prompting the first user to focus on the health data which makes more contribution.

Of course, the above-listed intention description data that can be used for estimating the query intention of the first user is only used for exemplary illustration and does not limit the scope of the present application.

Based on the above listed intention description data, different query intentions of the first user can be estimated, and different basic health data can be obtained, which will be exemplarily described below.

In an alternative embodiment, the first intent description data may include: the department to which the first user is affiliated and the second intent description data may include historical visits by the second user. The predicted query intention of the first user may be: and inquiring medical data corresponding to the target historical clinic of the second user.

The target historical visiting department refers to a historical visiting department matched with a visiting department affiliated to the first user in the historical visiting departments of the second user, namely the visiting department at which the second user visits currently. Optionally, the target historical visit department may include one historical visit department or a plurality of historical visit departments, and the embodiment is not limited. An embodiment of the pre-estimated target history visit department will be exemplarily described below with reference to the first intention description data and the second intention description data.

Optionally, the server 10 may calculate similarity between the department to which the first user belongs and at least one historical visiting department of the second user after acquiring the department to which the first user belongs and the at least one historical visiting department; then, selecting a target historical clinic from the at least one historical clinic, wherein the similarity of the target historical clinic and the clinic to which the first user belongs is greater than a set similarity threshold; then, medical data generated when the second user visits the target historical visiting department is obtained from the health data of the second user and used as basic health data.

In this embodiment, optionally, when the similarity between the department to which the first user belongs and the at least one historical clinic department is calculated, respectively, the code vector corresponding to the department to which the first user belongs may be obtained according to the diagnosis code of the disease contained in the department to which the first user belongs and tf-idf (term frequency-inverse text frequency index) corresponding to the diagnosis code; meanwhile, obtaining coding vectors corresponding to at least one historical clinic; then, the similarity between the coding vector corresponding to the department to which the first user belongs and the coding vector corresponding to each of the at least one historical visiting department is calculated respectively, so that the similarity between the department to which the first user belongs and the at least one historical visiting department is obtained.

In the following, an embodiment of calculating a code vector corresponding to a department will be exemplified by taking any department as an example, with reference to fig. 1 b.

Each department can diagnose a plurality of different diseases, and in order to obtain the coding vectors of the departments, the present embodiment can obtain the diagnosis codes corresponding to different disease types in the departments. The diagnosis code corresponding to the disease type includes, but is not limited to, International Classification of Diseases (ICD) code established by World Health Organization (WHO): ICD-10, ICD-9, or International Classification of Primary Care: ICPC 2. It should be noted that in some typical scenarios, different medical institutions and different departments may record disease diagnosis results in different ways, and the disease diagnosis results may be recorded in the form of ICD-10, ICD-9, ICPC2 or diagnosis names. Therefore, in the present embodiment, as shown in fig. 1b, when the code vector corresponding to each department is obtained, the description modes of the disease types in and among the departments can be unified in advance.

Optionally, in some embodiments, the disease types contained by the departments may be collectively described as ICD-10 codes or ICD-9 codes or other types of codes for each department, which is not limited by the present embodiment. Taking the unified description as the ICD-10 code as an example, the disease type originally described by the ICD-9 code can be converted into the ICD-10 code according to the corresponding table of ICD-9 and ICD-10; the disease type originally described by ICPC2 coding can be converted into ICD-10 coding according to the one-to-many relation between ICPC2 and ICD-10; if the disease type is originally described by the diagnosis name, the text similarity between the diagnosis name and the standard diagnosis name can be calculated to determine the standard diagnosis name corresponding to the diagnosis name, and the diagnosis name is converted into the ICD-10 code according to the corresponding table of the standard diagnosis name and the ICD-10 code.

After the diagnosis codes included in the departments are acquired for each department, tf-idf of each diagnosis code can be calculated as shown in fig. 1b, which will be described in detail below.

Wherein tf is used to calculate a normalized value of the frequency of occurrence of a diagnostic code in a department. Normalized frequency tf of diagnostic code i in department j_ijThe following equation 1 can be used for calculation:

in formula 1, i is a department code, j is a diagnosis code of a disease type, and n_ijTo diagnose the number of times, Σ, that code j appears in department i_kn_ikThe total number of all diagnostic codes in department i.

Among other things, idf is used to calculate the importance of a diagnostic code in distinguishing between different departments. If a diagnostic code is only present in certain departments, it is considered that the diagnostic code may make a greater contribution in distinguishing the departments. Idf of diagnostic code j_jThe calculation can be performed using the following equation 2:

in equation 2, | D | is the total number of all department codes involved in the calculation, | { i: j ∈ D_iJ is the number of departments containing the diagnostic code j, d_iIs the set of all diagnostic codes in department i. Based on equation 2, if the number of departments containing the diagnosis code j is smaller, the idf of the diagnosis code is smaller_jThe larger the value and thus the greater the weight of the visit code j in differentiating departments. For example, some diseases occur only in certain specialized departments, which have large idf values, and these specialized departments can be effectively distinguished by the disease.

Based on the above, the code j tf-idf is diagnosed in the department i_ijExpressed as: tf-idf_ij＝tf_ij×idf_jThe code vector of department i is denoted v_i＝[tf-idf_i1,tf-idf_i2,tf-idf_i3,...,tf-idf_iN]And N is the Nth diagnostic code in the department i, and N is a positive integer.

Based on the above embodiment, the code vector of the current department of the second user and the code vector corresponding to each historical department of the second user can be calculated. Then, the similarity between the code vector of the current department and the code vector of each historical department is calculated.

Optionally, the instant fruitIn the embodiment, when the similarity between the code vector of the current department and the code vector of each historical department is calculated, a cosine similarity meter algorithm may be used. For convenience of description, if the code vector of the current department is marked as v0 and the code vector of a certain historical department is marked as v1, the similarity between the two is determined

Where v1 · v0 denotes the dot product of the code vector v1 and the code vector v 0. Based on the calculated similarity, a historical department adapted to the current department may be selected from the at least one historical department as the first department.

When the query intention of the first user is estimated as: when the health data corresponding to the target historical clinic visit of the second user is inquired, the medical data generated when the second user visits the target historical clinic visit can be obtained from the health data corresponding to the second user and used as the basic health data.

One exemplary basic health data acquisition method is shown in fig. 1c, where the first user's historical visit department includes: historical visit department 1, historical visit department 2, historical visit department 3, historical visit department 4 …, each historical visit department containing a different medical record. When the department to which the first user of the first user belongs is obtained, the similarity between the department to which the first user belongs and each historical clinic department can be calculated respectively. As shown in fig. 1c, if the similarity between the department to which the first user belongs and the historical visiting department 1 and the historical visiting department 3 is greater than 0.5, the historical visiting department 1 and the historical visiting department 3 can be regarded as the target historical visiting department. Next, medical records can be screened, the medical records contained in the historical visit department 1 and the historical visit department 3 are used as basic health data, and the basic health data is sent to the client for display.

In addition to the above embodiments, in an alternative embodiment, the first intention description data may include: historical query behavior of the first user. Based on at least one of query sequence, query frequency and input query keywords when the first user queries different health data in the historical time period, the query preference of the first user can be calculated. When the first user queries at this time, the predicted query intention of the first user may be: and querying health data which is matched with the query preference of the first user in the health data of the second user. For example, in the history query process, a doctor prefers to query the history diagnosis and treatment plan of the patient preferentially, and at this time, the doctor may consider that the attention of the doctor to the history diagnosis and treatment plan of the patient is high. Therefore, the current query intention of the doctor can be estimated to be associated with the historical diagnosis and treatment plan of the patient. Then, historical diagnosis and treatment schemes can be obtained from the health data of the second user and used as basic health data, and the historical diagnosis and treatment schemes are sent to the client to be displayed.

In an alternative embodiment, the first intent description data may include: the first user's excellence in at least one of a field, historical encounter record, and the second intent description data may include historical encounter illness of the second user. The predicted query intention of the first user may be: and querying health data corresponding to the first historical diseases of the second user.

In such an embodiment, based on the domain, historical encounter record, that the first user is adept at, it may be inferred which diseases the first user is about to diagnose. Then, in the historical disease of the second user, the historical disease adapted to the disease to be diagnosed by the first user is determined as the first historical disease, and the health data corresponding to the first historical disease of the second user requested to be inquired by the first user is estimated. Next, health data corresponding to the first historical disease may be obtained from the health data of the second user as basic health data, and sent to the client for display.

In an alternative embodiment, the second intent description data may include: a distribution characteristic of the health data of the second user. According to the second intention description data, the estimated query intention of the first user may be: and inquiring the health data of which the proportion of the data quantity in the health data of the second user is greater than a set proportion threshold. As described above, the distribution characteristics of the health data of the second user can be represented by the data amount of the medical data corresponding to different disease types of the second user in the health data of the second user. If the proportion of the data amount of the medical data corresponding to one or more disease types in the health data of the second user is greater than a set proportion threshold (for example, 30 percent or 50 percent), it can be estimated that the first user requests to inquire the medical data. Next, the health data of which the proportion of the partial data volume is greater than the set proportion threshold value can be acquired as basic health data to actively prompt the first user to pay attention to the medical data corresponding to the partial disease type of the second user.

In an alternative embodiment, the second intent description data may include: a time of generation of the different health data of the second user. According to the second intention description data, the estimated query intention of the first user may be: the second user is queried for health data generated during the specified historical time period. The specified historical time period refers to a historical time period before the current visit of the second user, for example, three months, a half year, or a year before the current visit, and this embodiment is not limited. When the query intention is estimated, the health data generated by the second user in the appointed historical time period can be obtained and used as basic health data, and the basic health data is sent to the client side for displaying.

In an alternative embodiment, the second intent description data may include: frequency of queries for different health data of the second user. According to the second intention description data, the estimated query intention of the first user may be: and querying the health data of which the query frequency is greater than a set frequency threshold in the health data of the second user. The set frequency threshold may be set according to actual conditions, and this embodiment is not limited. When the query intention is estimated, the health data with the query frequency larger than the set frequency threshold in the health data of the second user can be obtained as basic health data, and the basic health data is sent to the client for displaying.

In some exemplary embodiments, the server 20 may further user-image the second user based on the second user's wellness data, thereby facilitating the first user to quickly learn about the second user's general wellness. As will be described in detail below.

In this embodiment, optionally, the server 20 may identify the health characteristics of the second user from the health data of the second user. Wherein the health characteristics may include: one or more of the characteristics of the visit behavior, the characteristics of the treatment means, the characteristics of the physical state and the characteristics of the life habit are adopted, and the embodiment is not limited. Based on the identified health characteristics, server 20 may generate at least one health-description label describing the health characteristics to describe the general health of the second user via the at least one health-description label. Server 20 may then use the at least one health description label as a result of the health analysis for the second user and send the at least one health description label to client 10 for presentation.

It should be noted that, in order to optimize the effect of the at least one health description label on the client 10, the at least one health description label may be divided into: a visit behavior label type, a treatment modality label type, a body state type, a life habit label type, and the like. Wherein, under each label type, one or more health description labels can be contained.

As will be exemplified below.

Optionally, the visit behavior feature may be expressed as: the number of visits by the second user within a set period of time, the time interval between adjacent visits, the medical institution at which the visit was made, the department at which the visit was made, etc. Accordingly, the following health description labels may be included under the visit behavior label types: the dermatology department has a diagnosis 2 times within three months, and the pneumology department has a diagnosis 3 times within half a year, etc.

Alternatively, the treatment means may be characterized by: the second user's experienced surgery, the drugs used, the body-implanted medical devices, and the like. Accordingly, under the treatment means label types, the following health description labels may be included: cardiac bypass surgery, hip surgery, amoxicillin, ampicillin, etc., implantation of cardiac pacemakers.

Optionally, the physical state characteristic may be represented by: the current disease, current physiological state, etc. of the second user. Accordingly, under the body state label type, the following health description label can be included: type II diabetes, liver and kidney insufficiency, elderly pregnant women, etc.

Alternatively, the life habit feature may be expressed as: the second user's living environment, work environment, eating habits, exercise habits, and the like. Accordingly, under the life habit tag type, the following health description tags can be included: take out frequently, exercise once a week, sit for 8 hours per day, etc.

After receiving the at least one health description label, the client 10 may display the at least one health description label in a label display area. A typical way of presenting a health description label in the label presentation area may be as shown in fig. 2 a.

Based on the way of displaying the health description labels, on one hand, based on at least one health description label, the first user can quickly know the approximate health condition of the second user; on the other hand, the first user can input his query intention through the at least one health description tag according to the actual data requirements, as will be described in detail below.

In an alternative embodiment, the first user may initiate a selection operation on the at least one health description label presented by the client 10. The client 10 obtains a health description label selected by the first user from the at least one health description label as a target health description label, and sends the target health description label to the server 20.

After receiving the target health description label, the server 20 may correct the pre-estimated query intent of the first user according to the target health description label. It should be understood that, after the query intent of the first user is modified, the server 20 may send the basic health data adapted to the modified query intent of the first user to the client 10 to update the presentation content of the client 10 in real time.

Based on the above embodiments, the server 20 may further identify at least one disease type of the second user's historical visits according to the second user's health data. Alternatively, the disease type identification process may be implemented based on the disease label described in the foregoing embodiment. For example, according to the cold label, the rhinitis label, the gastroenteritis label and the coronary heart disease label corresponding to the health data, the disease types of the second user in the historical treatment can be identified as follows: cold, rhinitis, gastroenteritis, coronary heart disease, etc.

Next, the server 20 may divide the at least one disease type into at least one disease group according to the disease group to which the disease type belongs. Alternatively, the dividing process of the disease group may be implemented based on the label of the disease group to which the disease belongs in the medical field described in the foregoing embodiment. For example, colds and rhinitis may be classified under respiratory illness groups according to respiratory illness labels on cold and rhinitis labels; for example, gastroenteritis may be classified under a group of digestive systems according to a digestive system disease label on the gastroenteritis label; for another example, coronary heart disease can be classified into circulatory groups according to the circulatory disease label on coronary heart disease.

Then, the server 20 may send the at least one disease group and the corresponding number of times of treatment thereof, and the disease type and the corresponding number of times of treatment thereof under each disease group as a health analysis result for the second user to the client 10 for presentation.

After receiving the health analysis result sent by the server 20, the client 10 may display at least one disease group and the corresponding number of visits included in the target health data in the medical history overview area. For example, icons such as "respiratory system (15)", "circulatory system (6)", "digestive system (4)", etc., as shown in FIG. 2a, may be presented in the medical history area. The disease grouping and corresponding number of visits may facilitate the first user to quickly learn about the second user's medical history

Optionally, the client 10 may present at least one disease type and the corresponding number of visits under the target disease group in response to the selection operation for the target disease group of the at least one disease group. For example, after the first user clicks on "respiratory system (15)" in the medical history area, the client 10 can display icons of "cold (8)", "rhinitis (2)", "bronchitis (5)", etc. under the respiratory system as shown in fig. 2 b.

Optionally, the client 20 may further determine a target disease type selected by the first user in response to the selection operation for the at least one disease type, and send the target disease type to the server 20.

After receiving the target disease type, the server 20 may modify the query intent of the first user according to the target disease type. It should be understood that, after the query intent of the first user is modified, the server 20 may send the basic health data adapted to the modified query intent of the first user to the client 10 to update the presentation content of the client 10 in real time.

On the basis of the above embodiments, the server 10 may further obtain the current symptom information of the second user. Then, at least one diagnosis suggestion for the second user is calculated according to the current symptom information of the second user and the corresponding health data of the second user, the at least one diagnosis suggestion is used as a health analysis result for the second user, and the at least one diagnosis suggestion is sent to the client 10 for displaying. Optionally, the at least one visit recommendation comprises: at least one of an inquiry recommendation, an examination item recommendation, a medication intake recommendation, and a diagnosis and treatment recommendation associated with the second user.

For example, when the current symptom information of the first user is headache and fever, and the health data of the second user indicates that the frequency of the second visit of the cold is high, the inquiry advice calculated by the server 20 may include: whether the patient has recently taken an antipyretic, whether the patient has recently visited a dense place of human flow, whether the patient has flu, and the like.

The client 10 may further present a suggestion presentation area. Alternatively, when the first user is implemented as a doctor and the second user is implemented as a patient, the client 10 may present at least one of a consultation recommendation, an examination item recommendation, a medication administration recommendation, and a diagnosis and treatment recommendation associated with the second user, which are transmitted by the server 20, in the presentation area. The diagnosis suggestion can assist the first user to quickly and definitely determine the diagnosis direction of the second user, and an efficient diagnosis process is realized.

Based on the above embodiments, when the server 20 sends the basic health data to the client 10, the basic health data may be classified into a plurality of data categories.

Optionally, in this embodiment, the plurality of data categories obtained by dividing may include: at least one of a syndrome category, a condition category, an examination category, an assay category, a treatment category, a surgery category, a drug category, an immunization category. Then, the server 20 may send the plurality of data types and the data corresponding to each of the plurality of data types to the client 10.

After the client 10 obtains the multiple data categories included in the basic health data, basic health data corresponding to a target data category in the multiple data categories may be displayed in the medical history detail display area. Meanwhile, the client 10 may also display view icons corresponding to a plurality of data categories for the first user to switch the data categories.

Fig. 2a and 2b illustrate a typical display manner of object data categories. As shown in fig. 2a and 2b, the medical history detail display area currently displays the "integrated" view icon and the integrated data under the icon, and simultaneously displays view icons corresponding to other data categories such as "disease", "assay", "examination", "surgery", "medicine", "immunization". If the first user wants to view the health data corresponding to the "operation" category, the "operation" view icon can be clicked to switch the health data corresponding to the "comprehensive" category being displayed into the basic health data corresponding to the "operation" category.

The target data category may be a default data category, may be a first data category for presetting, or may be a data category that the data processing system 100 preferentially recommends attention for the first user according to the viewing habit of the first user. The manner of determining the target data category will be exemplified below.

Alternatively, in a typical embodiment, the server 20 may obtain the historical viewing behavior of the first user, and then analyze the historical viewing behavior of the first user to obtain the interest scores of the first user for the plurality of data categories. The interest score corresponding to each data category is in positive correlation with the frequency of the first user preferentially viewing the health data of the data category in the historical query process.

Based on the interest scores of the plurality of data categories, the server 20 may determine, from among the plurality of data categories, a data category for which the interest score satisfies a set condition as a data category adapted to the historical viewing behavior of the first user, and send an instruction to preferentially present the data category adapted to the historical viewing behavior of the first user to the client 10.

After receiving the instruction, the client 10 may determine a data category adapted to the historical viewing behavior of the first user as a target data category, and preferentially display the basic health data corresponding to the target data category in the medical history detail display area. For example, if a first user frequently prefers to view underlying health data under the "drugs" data category during historical queries, data processing system 100 may prefer to show underlying health data under the "drugs" data category for their recommendations during current or future queries to optimize query efficiency.

It should be appreciated that the health data of the second user may include medical data from multiple visits by the user or a physical examination report from multiple physical examinations. That is, the underlying health data may include at least one medical history associated with a time. The medical history records refer to information for simply describing cases. Typically, a history record may include the medical institution, department, type of visit (outpatient, emergency, in-patient).

Based on this, optionally, after the client 10 acquires the basic health data, the at least one medical history record may be displayed in a time axis display form in a medical history detail display area according to the visit time sequence corresponding to the at least one medical history record included in the basic health data, so as to facilitate viewing.

It should be noted that when the client 10 displays a plurality of data categories included in the basic health data, at least one medical history record under each data category can be displayed in the form of a time axis. Meanwhile, when each medical history record in the target data category is displayed, the data label of the detailed data corresponding to the medical history record and the disease condition description keyword of the user can be displayed. For example, as shown in fig. 2a and 2b, when a medical history record in the data category of "integrated" is displayed, data labels such as "impacted tooth", "X-ray", "caries" and the like can be displayed in a case record of "first hospital/department of stomatology/clinic". For example, the "conditions" shown in fig. 2a and 2 b: frequently toothache, inability to eat spicy food and other disease condition description keywords.

In some exemplary embodiments, the client 10 can highlight one portion of the medical history record and collapse another portion of the medical history record. As will be described in detail below.

Optionally, before the server 20 sends the basic health data to the client 10 for presentation, the relevance between at least one medical history record contained in the basic health data and the query intention of the first user may be calculated respectively. After receiving the association degrees corresponding to the at least one medical history record, the client 10 may prominently display the medical history record whose association degree with the query intention of the first user is greater than or equal to a set threshold, and fold and display the medical history record whose association degree with the query intention of the first user is less than the set threshold.

The server 20 can be implemented by combining at least one of the intention description data described in the foregoing embodiments when calculating the association degree between each medical history record and the query intention of the first user. Taking any of the at least one medical history record as an example, optionally, the server 20 can obtain detailed data corresponding to the medical history record. Wherein the detail data may include: the medical history record contains specific disease description data, specific diagnosis result data, specific prescription data, medical order data, and the like. Alternatively, the detailed data may be from a case, medical record, or medical history recorded by the physician at the time of the patient visit.

Then, the server 20 may calculate the correlation between the detail data and the at least one intention description data, respectively, to obtain at least one correlation calculation result. Wherein the at least one intent description data may comprise: the first intention description data and/or the second intention description data refer to the descriptions of the foregoing embodiments, and are not repeated herein. Alternatively, the server 20 may calculate the correlation degree between the data tag corresponding to the detail data and the data tag corresponding to the intention description data, or may calculate the correlation degree between the text of the detail data and the text of the intention description data based on a text recognition method, which is described herein in detail.

Next, the server 20 can perform a weighted summation on the at least one correlation calculation result according to the respective corresponding weights of the at least one intention description data to obtain the correlation between the medical history record and the query intention of the first user. Similarly, the server 20 can calculate the association degree between each medical history record and the query intention of the first user, and send the calculated association degree corresponding to each of the at least one medical history record to the client 10.

FIG. 2a and FIG. 2b illustrate a typical presentation of medical records, and as shown in FIG. 2a and FIG. 2b, a fold icon is displayed on the time axis, showing that 99 medical records are folded. The second user can click the fold icon to view the folded medical history.

Optionally, for any one of the at least one medical history record, the client 10 can also display a detail view icon corresponding to the medical history record in a medical history detail display area, as shown in fig. 2a and fig. 2 b. Furthermore, if the first user wants to view the details corresponding to the medical history record, the first user can trigger a details viewing icon corresponding to the medical history record.

When the client 10 detects a trigger action for the details view icon, a details page of the medical history record may be presented in response to the trigger action. On the details page of the medical history record, the client 10 can display the corresponding details data of the medical history record in the form of text, picture, table and/or chart. Wherein the picture may be an image of a medical record prescribed by a medical institution. Among others, charts may include, but are not limited to: a bar graph (histogram), a line graph, a pie graph, a bar graph, a radar chart, etc., but the present embodiment includes but is not limited thereto.

FIG. 3a is a diagram showing the detailed data of a history record of "blood routine + liver function 3" in the data category of "test" in a table. As shown in fig. 3a, the table includes detailed data of each test item and its corresponding measurement result, unit, reference value, and the like.

FIG. 3b is a chart showing details of a "bacterial culture + drug sensitivity" history record in the data category "assay" in a tabular manner. As shown in fig. 3b, the table includes details of the identification results, drug sensitivity results, and the like.

Figure 3c illustrates the detailed data in the data category "drugs" presented in a bar graph. As shown in FIG. 3c, the bar graph may show the type of medication taken by the patient over a period of time, the length of time the medication was taken, and the conflict between medications. Each icon for displaying the medication duration may display details of the medication duration, such as a specific medication start date, after the trigger information is detected, and will not be described any further.

In addition, as shown in fig. 3c, when the detailed data under the data category of "drug" is displayed, the allergy information of the patient can be further displayed. In fig. 3c, the allergy information of the patient can be displayed in a classified manner, so that the allergy condition of the patient can be more clearly understood, and the prescription can be provided by the doctor according to the disease condition and the allergy condition of the patient during the diagnosis.

It is worth noting that in some exemplary embodiments, when the details page of the medical history record is presented, the client 10 can further highlight the data that the first user may be more interested in or contribute more to the first user's actual business. As will be described in detail below.

Optionally, in such an embodiment, the server 20 may further obtain the current symptom information of the second user. The current condition information may be manually entered by the first user, or captured by an audio device installed on the client 10, or actively acquired by the server 20. For example, when the second user is implemented as a patient for a visit, the server 20 may obtain current symptom information provided by the patient at the time of registration or triage through a third party registration platform.

For any of the at least one medical history record, the server 20 may identify, by using a Natural Language Processing (NLP), a part of the detail data corresponding to the medical history record, which is adapted to the current medical condition information of the second user, and then send an identification of the part of the detail data to the client 10.

After receiving the identifier of the part of the detail data, the client 10 may highlight, in a detail page of the medical history record, part of the detail data corresponding to the medical history record, which is adapted to the current medical condition information of the second user. Based on the implementation, the first user can quickly acquire data which is more concerned by the first user or data which has larger contribution to the actual business of the first user.

For example, if the patient's condition is cough, the server 20 may determine, based on a text recognition and matching algorithm, drug information that matches the cough condition from the detail data corresponding to the patient's medical history record, and send an identification of the drug information to the client 10. Further, the client 10 can highlight which cough-treating medicines the patient has taken in the past, so as to facilitate the diagnosis by the doctor.

It should be noted that, on the basis of the above embodiments, as shown in fig. 2a and fig. 2b, the client 10 may further display a filtering icon in the query setting area, so that the first user can input the filtering condition of the health data. Optionally, the client 10 may display a filtering interface after the filtering icon is triggered, and the first user may input the filtering conditions such as the type of medical treatment, the medical institution, the medical department, and the like in the filtering interface, which is not illustrated.

Based on the above embodiments, as shown in fig. 2a and fig. 2b, the client 10 may further present an optional health data query time period in the query setting area for the first user to select. As shown in fig. 2a and 2b, the first user may set to query the health data for the entire time period, the health data for the last three months, the health data for the last six months, or the health data for the last year.

Based on the above embodiments, as shown in fig. 2a and fig. 2b, the client 10 may display a query time customization control in the query setting area, so that the first user can customize the query time period of the health data.

On the basis of the above embodiments, as shown in fig. 2a and 2b, the client 10 may display a search component in the query setting area, so that the first user may input a search keyword for the health data, which is not described again.

In some exemplary embodiments, the data processing system 100 may set different query terms for different querying users. For example, for a doctor, the query authority can be set as follows: and inquiring health data corresponding to the department to which the doctor belongs in the health data of the user, or inquiring health data matched with the main treatment field of the doctor in the health data of the user. For example, for a pharmacy staff, the query authority can be set as follows: and inquiring data related to the diagnosis and treatment prescription in the health data of the user. For example, for a medical subsidy processing user, the query authority can be set as follows: and inquiring the medical record of the disease and the data related to the charging record which accord with the medical subsidy condition in the health data of the user. For example, for a work injury reimbursement handler, the query authority can be set as: and inquiring the health data of the user, and authenticating the health data as relevant data of the industrial injury diseases. For another example, for the underwriters and claims processors of the commercial insurance company, the query authority can be set as follows: and querying related data of medical records in the health data of the user, which influence the past medical history of the insurance, or querying related data of diseases for which the user applies for claim settlement, wherein the data is not repeated.

Based on this, after receiving the query operation of the first user, the client 10 may obtain the identity information of the first user, and send the identity information of the first user to the server 20. Typically, the identity information may include a query account number that is pre-registered and authorized for use. The server 20 may determine the query authority of the first user according to the identity information of the first user. And then, determining health data adaptive to the query authority of the first user from the health data corresponding to the second user, and acquiring the health data adaptive to the query intention of the first user from the health data adaptive to the query authority of the first user as target health data, which is not described in detail.

In some exemplary embodiments, the first user may be implemented as the same user as the second user, who may be aware of his or her health data based on the data processing system 100 provided in the foregoing embodiments. Further, the data processing system 100 may also provide a health reminder function to the user, as will be illustrated below.

In some alternative embodiments, the user may enter the medication currently being taken by the user via the client 10. After obtaining the medicine, the client 10 or the server 20 may query the administration period and the administration frequency of the medicine, and calculate the administration time of the medicine based on the administration period and the administration frequency. Next, when the medication taking time of the medication reaches, the client 10 outputs a medication taking reminding message to remind the user to take the medication at a proper time, so as to complete the diagnosis and treatment process.

Optionally, the medicine taking reminding message output by the client 10 may indicate that the medicine taking time of the user is up, please take the medicine on time, and may further remind the user of the number of medicines to be taken, the medicine taking precautions (warm water/cold water, before meal/after meal), and the like, which are not described again.

In still other alternative embodiments, the client 10 may also present a health recommendation for the second user. Wherein the health advice may be generated by the server 20 based on the second user's physical examination report data. For example, if the physical examination report of the second user indicates that the liver health of the second user is impaired, the client 10 may remind the second user to avoid staying up all night, drinking a little, and the like; for another example, if the physical examination report of the second user indicates that the second user has poor immunity, the client 10 may remind the user to exercise his or her health, balance diet, and so on, and will not be described in detail.

In addition to the data processing system described in the above embodiments, the embodiments of the present application also provide a data processing method, which will be described in detail below.

Fig. 4 is a flowchart illustrating a data processing method according to another exemplary embodiment of the present application, which when executed on a client side, may include the steps shown in fig. 4:

step 401, in response to the operation of querying the health data of the second user by the first user, obtaining the target health data of the second user from the server.

Step 402, at least one basic information display area and at least one analysis result display area are displayed on a first page.

Step 403, in the at least one basic information display area, displaying the basic health data in the target health data in a classified manner, and in the at least one analysis result display area, displaying the health analysis results in the target health data in a classified manner.

In some exemplary embodiments, in the at least one analysis result presentation area, the health analysis results in the target health data are presented in a classified manner, including at least one of: displaying at least one disease group and the corresponding number of times of treatment corresponding to the second user in the medical history overview area; displaying at least one health description label of the second user in a label display area; and displaying the health advice for the second user in an advice display area, wherein the health advice is generated according to the physical examination report data of the second user.

In some exemplary embodiments, displaying at least one disease group and the number of visits corresponding to the second user in the medical history overview area further includes: and responding to the selection operation of the target disease group in the at least one disease group, and displaying at least one disease type and the corresponding number of times of treatment under the target disease group in the medical history overview area.

In some exemplary embodiments, in the at least one basic information presentation area, a manner of categorically presenting basic health data in the target health data includes: acquiring a plurality of data categories contained in the basic health data; and displaying the view icons corresponding to the multiple data categories and the basic health data corresponding to the target data category in the multiple data categories in the medical history detail display area.

In some exemplary embodiments, in the medical history detail display area, one way of displaying the view icons corresponding to the plurality of data categories and the basic health data corresponding to the target data category in the plurality of data categories comprises: acquiring at least one medical history record contained in the target data category; and displaying the at least one medical history record in a time shaft display form in the medical history detail display area according to the visit time sequence corresponding to the at least one medical history record.

In some exemplary embodiments, presenting the at least one medical history record in an presentation of a timeline further comprises: highlighting the medical history record with the relevance degree of the query intention of the first user being greater than or equal to a set threshold value, and folding and showing the medical history record with the relevance degree of the query intention of the first user being smaller than the set threshold value.

In some exemplary embodiments, for any of the at least one medical history record, further comprising: displaying a detail viewing icon corresponding to the medical history record in the medical history detail display area; responding to the triggering operation aiming at the detail viewing icon, and displaying a detail page of the medical history record; and displaying the detailed data corresponding to the medical history record in the form of text, picture, table and/or chart on the detailed page of the medical history record.

In some exemplary embodiments, the method further comprises: acquiring current symptom information of the second user; and highlighting part of the detail data matched with the current disease information of the second user in the detail data corresponding to the medical record in the detail page of the medical record.

In some exemplary embodiments, the target health data comprises a plurality of data categories including: at least one of a syndrome category, a condition category, an examination category, an assay category, a treatment category, a surgery category, a drug category, an immunization category.

In some exemplary embodiments, the method further comprises: acquiring the currently taken medicine of the second user; when the medicine taking time of the medicine is up, outputting a medicine taking reminding message; wherein, the taking time of the medicine is calculated according to the taking period and the taking times of the medicine.

In some exemplary embodiments, the method further comprises: displaying a screening icon in the query setting area so that the first user can input screening conditions of the health data; and/or, presenting an optional health data query time period in the query setting area for selection by the first user; and/or, displaying a query time self-defining control in the query setting area so as to enable the first user to define the query time period of the health data; and/or, a search component is presented in the query setting area for the first user to input search keywords for the health data.

In this embodiment, when the first user requests to query the health data of the second user, the client may display the target health data in a classified manner in at least one information display area on the first page according to the category to which the target health data of the second user belongs. Furthermore, the first user can rapidly acquire the health data meeting the query requirement according to the classified and displayed target health data, and the data query efficiency is improved.

Fig. 5a is a flowchart illustrating a data processing method according to another exemplary embodiment of the present application, where the method, when executed on a server side, may include the steps shown in fig. 5 a:

step 501a, receiving a data acquisition request, where the data acquisition request is sent by a client when a first user queries health data of a second user.

Step 502a, obtaining basic health data and health analysis results in the health data of the second user as target health data according to the data obtaining request.

Step 503a, sending the target health data to the client for displaying.

In some exemplary embodiments, one way of obtaining the underlying health data in the health data of the second user according to the data obtaining request includes: acquiring a department to which the first user belongs and at least one historical clinic department of the second user; respectively calculating the similarity between the department to which the first user belongs and the at least one historical clinic department; selecting a target historical clinic from the at least one historical clinic, wherein the similarity of the target historical clinic and the clinic to which the first user belongs is greater than a set similarity threshold; and acquiring medical data generated when the second user visits the target historical visiting department from the health data of the second user as the basic health data.

In some exemplary embodiments, one way of separately calculating the similarity of the department to which the first user is affiliated and the at least one historical visit department comprises: acquiring a code vector corresponding to the department to which the first user belongs according to the diagnosis code of the disease type contained in the department to which the first user belongs and tf-idf corresponding to the diagnosis code; acquiring coding vectors corresponding to the at least one historical clinic; and respectively calculating the similarity between the coding vector corresponding to the department to which the first user belongs and the coding vector corresponding to each of the at least one historical visiting department so as to obtain the similarity between the department to which the first user belongs and the at least one historical visiting department.

In some exemplary embodiments, a way of obtaining health analysis results in the health data of the second user includes: identifying health characteristics of the second user according to the health data of the second user; and generating at least one health description label of the second user as the health analysis result according to the health characteristics.

In some exemplary embodiments, the health characteristics include: one or more of a visit behavior characteristic, a treatment means characteristic, a physical state characteristic, and a life habit characteristic.

In some exemplary embodiments, a way of obtaining health analysis results in the health data of the second user includes: identifying at least one disease type of the second user's historical visits based on the second user's health data; dividing the at least one disease type into at least one disease group according to the disease group to which the disease type belongs; and taking the at least one disease group and the corresponding number of times of treatment as the health analysis result.

In some exemplary embodiments, a way of obtaining health analysis results in the health data of the second user includes: acquiring current symptom information of the second user; calculating at least one diagnosis suggestion for the second user according to the current symptom information of the second user and the health data corresponding to the second user, and sending the at least one diagnosis suggestion to the client for displaying; wherein the at least one visit recommendation comprises: at least one of an inquiry recommendation, an examination item recommendation, a medication intake recommendation, and a diagnosis and treatment recommendation associated with the second user.

In some exemplary embodiments, a manner of sending the target health data to the client for presentation includes: classifying the basic health data to obtain a plurality of data classes; the plurality of data categories include: at least one of a syndrome category, a condition category, an examination category, an assay category, a treatment category, a surgery category, a drug category, an immunization category; and sending the multiple data types and the data corresponding to the multiple data types to the client for display.

In some exemplary embodiments, further comprising: acquiring historical viewing behaviors of the first user; analyzing the historical viewing behavior of the first user to obtain interest scores of the first user on the plurality of data categories; determining a data category with an interest score satisfying a set condition from the plurality of data categories as a target data category; and sending an instruction for preferentially displaying the target data category to the client.

In some exemplary embodiments, the target data category includes at least one medical history record; for any of the at least one medical history, the method further comprises: acquiring current symptom information of the second user; identifying partial detailed data matched with the current symptom information of the second user in the detailed data corresponding to the medical history record by adopting a natural language processing algorithm; and sending the identification mark of the part of the detail data to the client so that the client can highlight the part of the detail data.

In this embodiment, when a data acquisition request sent by a client is received, the basic health data and the health analysis result in the health data of the second user can be acquired according to the data acquisition request and used as the target health data, and the target health data is displayed through the client, so that the multi-dimensional and multi-angle flexible display of the health data is realized, the first user is assisted to quickly know the health state of the second user, and the data query efficiency is improved.

Fig. 5b is a flowchart illustrating a data processing method according to another exemplary embodiment of the present application, where the method, when executed on the server side, may include the steps shown in fig. 5 b:

step 501b, receiving a data acquisition request, where the data acquisition request is sent by a client when a first user queries health data of a second user, and the data acquisition request carries identity information of the first user.

Step 502b, if the first user is identified as a medical subsidy processing user according to the identity information of the first user, obtaining diagnosis and treatment records and diagnosis and treatment expense data corresponding to the target disease type meeting the medical subsidy condition from the health data of the second user.

Step 503b, sending the diagnosis and treatment records and the diagnosis and treatment cost data corresponding to the target disease type to a client for displaying so as to be viewed by the first user.

When a first user initiates an operation of inquiring the health data of a second user through a client, the identity information of the first user can be provided. For example, when the first user initiates a query operation, a login account and a password, or other authorized identification may be provided as the identity information.

After acquiring the identity information of the first user, the client may add the identity information to the data acquisition request, and send the data acquisition request to the server. When the server estimates the query intention of the first user according to the data acquisition request sent by the client, the server can acquire the identity information of the first user carried by the data acquisition request and estimate the query intention of the first user according to the identity information of the first user.

In some optional embodiments, if the server identifies the first user as a medical subsidy processing user according to the identity information of the first user, the server may estimate that the query intent of the first user is: and inquiring the target disease type meeting the medical subsidy condition.

Optionally, a corresponding medical subsidy processing account and a password may be allocated to the medical subsidy processing user in advance, and when the server recognizes that the identity information input by the first user includes the medical subsidy processing account, and the password is matched with the account, it may be determined that the first user is the medical subsidy processing user. Or the medical subsidy processing user's identification identifier such as job number, organization code or identification number can be pre-entered, and when the first user initiates the query operation, the user is prompted to enter the identification identifier. After the identification input by the user is obtained, consistency verification can be carried out according to the identification input in advance, and the first user can be determined as a medical subsidy processing user when the consistency verification passes.

Based on this, when the server acquires the health data adapted to the query intention of the first user from the health data corresponding to the second user, the server may acquire the diagnosis and treatment record and the diagnosis and treatment cost data corresponding to the target disease type satisfying the medical subsidy condition from the health data of the second user as the target health data. The server may then send the target health data to the client for presentation. The medical subsidy conditions are preset, and the medical subsidy conditions in different regions or different administrative areas are different, so that the medical subsidy conditions can be set differently according to the region or the administrative area to which the user belongs, and the details are omitted in this embodiment.

Based on the above, the disease type corresponding to the second user can be obtained from the health data of the second user, and then the disease type meeting the preset medical subsidy condition is determined from the disease types. And then, acquiring diagnosis and treatment records and diagnosis and treatment cost corresponding to the disease type for displaying so as to be checked by the first user.

The embodiment has the advantages that a channel for quickly inquiring the health data of the subsidized user is provided for the medical subsidizing user, so that the processing efficiency of the medical subsidizing is improved, and the real reliability of the diagnosis and treatment records of the subsidized user is ensured.

Fig. 5c is a flowchart illustrating a data processing method according to another exemplary embodiment of the present application, where the method, when executed on the server side, may include the steps shown in fig. 5 c:

step 501c, receiving a data acquisition request, where the data acquisition request is sent by a client when a first user queries health data of a second user, and the data acquisition request carries identity information of the first user.

Step 502c, if the first user is identified as the commercial insurance processing user according to the identity information of the first user, an authorization request is sent to the second user according to the identity information of the first user.

Step 503c, if receiving the authorization notification message returned by the second user according to the authorization request, obtaining the health data associated with the commercial insurance from the health data of the second user.

Step 504c, sending the health data associated with the commercial insurance to a client for presentation for viewing by the first user.

The server identifies the first user as a business insurance processing user according to the identity information of the first user, and then the server can estimate that the query intention of the first user is as follows: health data associated with the commercial insurance is queried. The business insurance processing user can be realized as a salesman of a business insurance company. When the second user applies for insurance application, renewal or insurance claim settlement service, the first user can inquire the health data of the second user to ensure that the second user can be accurately and efficiently provided with the service.

Optionally, the health data associated with the commercial insurance may include: health data of the second user when the second user puts insurance, health data of the second user when the second user continues putting insurance, or health data of the second user when applying for insurance claims.

Alternatively, the specific query as to which type of health data associated with the commercial insurance is provided by the first user on an active basis. For example, the plurality of query intent options may be presented for user input or the intent input box may be presented for user input when the first user initiates a query operation. Optionally, because the contents of services processed by different service providers are different, the present embodiment may assign different accounts to the service providers processing different services. For example, an insurance check account is allocated to a user who handles insurance check, and a claim check account is allocated to a user who handles insurance claim check. Based on this, when the first user initiates the query operation, the account of the first user may be obtained, and the specific query intention of the first user is obtained based on the service type corresponding to the account.

Based on the above, when the server obtains the health data adapted to the query intention of the first user from the health data corresponding to the second user, the server may send an authorization request to the second user in advance according to the query intention of the first user. Optionally, in this embodiment, the query intention of the first user may be sent to the first user in the form of a short message, a telephone call, or a terminal push message to request the first user to authorize the behavior. And when the second user returns the authorization notification message according to the authorization request, displaying the data which is matched with the query intention of the first user in the health data of the second user.

If receiving the authorization notification message returned by the second user according to the authorization request, the server 20 obtains the health data associated with the commercial insurance from the health data of the second user.

Based on the mode of requesting authorization from the user, the efficiency of insurance application check, renewal check and claim settlement check can be effectively improved while the information security of the user is ensured.

Fig. 5d is a flowchart illustrating a data processing method according to another exemplary embodiment of the present application, where the method, when executed on the server side, may include the steps shown in fig. 5 d:

step 501d, receiving a data acquisition request, where the data acquisition request is sent by a client when a first user queries health data, and the data acquisition request carries identity information of the first user.

And 502d, if the first user is identified as a disease control user in a set regional scope according to the identity information of the first user, acquiring medical data of a plurality of medical institutions in the set regional scope.

Step 503d, calculating the disease distribution characteristics in the set region range according to the medical data.

And step 504d, sending the disease distribution characteristics to a client for displaying so as to be viewed by the first user.

The server identifies that the first user is a disease control user in a set region range according to the identity information of the first user, and then the server can estimate that the query intention of the first user is as follows: request to inquire the disease distribution characteristics in the set region range.

The disease control user can be a worker of a disease control center or a health and epidemic prevention department. Based on the present embodiment, prevention of a specific disease (e.g., a pandemic disease) can be facilitated. The set area range may be an area range obtained by dividing the set area range according to a geographical area, or an area range obtained by dividing the set area range according to an administrative area, which is not limited in this embodiment.

Based on the above, when the server obtains the health data adapted to the query intention of the first user from the health data corresponding to the second user, the server may obtain medical data of a plurality of medical institutions belonging to the set geographical range of the second user, and calculate the disease distribution characteristics within the set geographical range according to the medical data. Wherein the second user may comprise a plurality of users.

Alternatively, for each geographic area, the server may analyze the frequency of visits for each disease within the geographic area. Based on the number of times of seeing a doctor, the high-incidence diseases in the region range can be determined, so that relevant departments can specify and take corresponding disease control means.

Optionally, for each geographical area, the server may analyze the visit period for each disease within the geographical area. Based on the treatment time period, the opening time of the medical institution and the current staff ratio can be adjusted to meet the treatment requirement.

Alternatively, for each geographic area, the server may analyze the medical facilities of each disease within the geographic area. Based on the analysis result of the medical institution, measures such as diversion, shunt and the like can be executed on the medical institution with larger treatment flow.

Alternatively, for each geographical area, the server may analyze and calculate the age of onset of each disease within the geographical area. Based on the age group analysis result, the age group with high incidence of the disease can be determined, so as to be beneficial to developing new medicines, adjusting medical resource distribution and the like.

After the disease distribution characteristics in the set region range are obtained through calculation, the disease distribution characteristics can be sent to the client side for visual display. Optionally, when the client visually displays the disease distribution characteristics, the client may display the disease distribution characteristics through a plurality of data charts, for example, a line graph, a pie graph, a bar graph, and the like, so as to visually display the distribution characteristics of each disease of the disease, which is not described again.

Optionally, in this embodiment, the server may further calculate a target disease with a frequency of seeing a doctor greater than a set frequency threshold according to the disease distribution characteristic, and output an early warning message for the target disease. The method for outputting the early warning message may include: the early warning message for the target disease is sent to the client, the early warning short message for the target disease is sent to the user in the set region range, the early warning message for the target disease is pushed to the terminal of the user in the set region range, or a disease epidemic prevention early warning notice can be sent to a disease control department in the set region range, which is not repeated.

Based on the scheme provided by the embodiment, the disease control user can find the disease distribution characteristics of different regions in time, and can conveniently prevent specific diseases (such as epidemic diseases).

It should be noted that the execution subjects of the steps of the methods provided in the above embodiments may be the same device, or different devices may be used as the execution subjects of the methods. For example, the execution subjects of step 201 to step 204 may be device a; for another example, the execution subject of steps 201 and 202 may be device a, and the execution subject of step 203 may be device B; and so on.

In addition, in some of the flows described in the above embodiments and the drawings, a plurality of operations are included in a specific order, but it should be clearly understood that the operations may be executed out of the order presented herein or in parallel, and the sequence numbers of the operations, such as 201, 202, etc., are merely used for distinguishing different operations, and the sequence numbers do not represent any execution order per se. Additionally, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first", "second", etc. in this document are used for distinguishing different messages, devices, modules, etc., and do not represent a sequential order, nor limit the types of "first" and "second" to be different.

Fig. 6 is a schematic structural diagram of a health data display device according to an exemplary embodiment of the present application, and as shown in fig. 6, the health data display device may include:

the obtaining module 601 is configured to obtain target health data of a second user from a server in response to an operation of querying health data of the second user by a first user.

A presentation module 602, configured to present at least one basic information presentation area and at least one analysis result presentation area on a first page; in the at least one basic information display area, basic health data in the target health data are displayed in a classified mode, and in the at least one analysis result display area, health analysis results in the target health data are displayed in a classified mode.

Further optionally, the display module 602 comprises: the medical history overview sub-module 6021 is configured to display at least one disease group and the corresponding number of times of treatment corresponding to the second user in the medical history overview region; a tag display sub-module 6022 for displaying at least one health description tag of the second user in a tag display area; a suggestion presentation sub-module 6023 for presenting health suggestions for the second user in a suggestion presentation area, the health suggestions generated based on the physical examination report data of the second user.

Further optionally, the medical history overview sub-module 6021 is further configured to, when the medical history overview region shows at least one disease group and the corresponding number of times of visit corresponding to the second user, further: and responding to the selection operation of the target disease group in the at least one disease group, and displaying at least one disease type and the corresponding number of times of treatment under the target disease group in the medical history overview area.

Further optionally, the presentation module 602 includes a medical history detail presentation sub-module 6024 for: acquiring a plurality of data categories contained in the basic health data; and displaying the view icons corresponding to the multiple data categories and the basic health data corresponding to the target data category in the multiple data categories in the medical history detail display area.

Further optionally, the medical history detail display sub-module 6024, when displaying the view icons corresponding to the multiple data categories and the basic health data corresponding to the target data category in the multiple data categories in the medical history detail display area, is specifically configured to: acquiring at least one medical history record contained in the target data category; and displaying the at least one medical history record in a time shaft display form in the medical history detail display area according to the visit time sequence corresponding to the at least one medical history record.

Further optionally, the history detail display sub-module 6024 displays the at least one history record in a display form of a time axis, and is further configured to: highlighting the medical history record with the relevance degree of the query intention of the first user being greater than or equal to a set threshold value, and folding and showing the medical history record with the relevance degree of the query intention of the first user being smaller than the set threshold value.

Further optionally, for any of the at least one medical history record, the medical history detail presentation sub-module 6024 is further configured to: displaying a detail viewing icon corresponding to the medical history record in the medical history detail display area; responding to the triggering operation aiming at the detail viewing icon, and displaying a detail page of the medical history record; and displaying the detailed data corresponding to the medical history record in the form of text, picture, table and/or chart on the detailed page of the medical history record.

Further optionally, the history detail display sub-module 6024 is further configured to: acquiring current symptom information of the second user; and highlighting part of the detail data matched with the current disease information of the second user in the detail data corresponding to the medical record in the detail page of the medical record.

Further optionally, the target health data comprises a plurality of data categories including: at least one of a syndrome category, a condition category, an examination category, an assay category, a treatment category, a surgery category, a drug category, an immunization category.

Further optionally, the display module 602 further includes a reminder sub-module 6025 configured to: acquiring the currently taken medicine of the second user; when the medicine taking time of the medicine is up, outputting a medicine taking reminding message; wherein, the taking time of the medicine is calculated according to the taking period and the taking times of the medicine.

Further optionally, the apparatus further comprises a query setting sub-module 603 configured to: displaying a screening icon in the query setting area so that the first user can input screening conditions of the health data; and/or, presenting an optional health data query time period in the query setting area for selection by the first user; and/or, displaying a query time self-defining control in the query setting area so as to enable the first user to define the query time period of the health data; and/or, a search component is presented in the query setting area for the first user to input search keywords for the health data.

Fig. 7 is a schematic structural diagram of a health data display device according to another exemplary embodiment of the present application, and as shown in fig. 7, the health data display device may include:

a receiving module 701, configured to receive a data obtaining request, where the data obtaining request is sent by a client when a first user queries health data of a second user.

A data obtaining module 702, configured to obtain, according to the data obtaining request, basic health data and a health analysis result in the health data of the second user as target health data; .

A sending module 703, configured to send the target health data to the client for displaying.

Further optionally, when the data obtaining module 702 obtains the basic health data in the health data of the second user according to the data obtaining request, it is specifically configured to: acquiring a department to which the first user belongs and at least one historical clinic department of the second user; respectively calculating the similarity between the department to which the first user belongs and the at least one historical clinic department; selecting a target historical clinic from the at least one historical clinic, wherein the similarity of the target historical clinic and the clinic to which the first user belongs is greater than a set similarity threshold; and acquiring medical data generated when the second user visits the target historical visiting department from the health data of the second user as the basic health data.

Further optionally, when the data obtaining module 702 respectively calculates the similarity between the department to which the first user belongs and the at least one historical visiting department, it is specifically configured to: acquiring a code vector corresponding to the department to which the first user belongs according to the diagnosis code of the disease type contained in the department to which the first user belongs and tf-idf corresponding to the diagnosis code; acquiring coding vectors corresponding to the at least one historical clinic; and respectively calculating the similarity between the coding vector corresponding to the department to which the first user belongs and the coding vector corresponding to each of the at least one historical visiting department so as to obtain the similarity between the department to which the first user belongs and the at least one historical visiting department.

Further optionally, when the data obtaining module 702 obtains the health analysis result in the health data of the second user, it is specifically configured to: identifying health characteristics of the second user according to the health data of the second user; and generating at least one health description label of the second user as the health analysis result according to the health characteristics.

Further optionally, the health characteristics include: one or more of a visit behavior characteristic, a treatment means characteristic, a physical state characteristic, and a life habit characteristic.

Further optionally, when the data obtaining module 702 obtains the health analysis result in the health data of the second user, it is specifically configured to: identifying at least one disease type of the second user's historical visits based on the second user's health data; dividing the at least one disease type into at least one disease group according to the disease group to which the disease type belongs; and taking the at least one disease group and the corresponding number of times of treatment as the health analysis result.

Further optionally, when the data obtaining module 702 obtains the health analysis result in the health data of the second user, it is specifically configured to: acquiring current symptom information of the second user; calculating at least one diagnosis suggestion for the second user according to the current symptom information of the second user and the health data corresponding to the second user, and sending the at least one diagnosis suggestion to the client for displaying; wherein the at least one visit recommendation comprises: at least one of an inquiry recommendation, an examination item recommendation, a medication intake recommendation, and a diagnosis and treatment recommendation associated with the second user.

Further optionally, when the sending module 703 sends the target health data to the client for displaying, the sending module is specifically configured to: classifying the basic health data to obtain a plurality of data classes; the plurality of data categories include: at least one of a syndrome category, a condition category, an examination category, an assay category, a treatment category, a surgery category, a drug category, an immunization category; and sending the multiple data types and the data corresponding to the multiple data types to the client for display.

Further optionally, the apparatus further comprises: the data processing module 704 is specifically configured to: acquiring historical viewing behaviors of the first user; analyzing the historical viewing behavior of the first user to obtain interest scores of the first user on the plurality of data categories; determining a data category with an interest score satisfying a set condition from the plurality of data categories as a target data category; the sending module 703 is further configured to: and sending an instruction for preferentially displaying the target data category to the client.

Further optionally, the target data category comprises at least one medical history record; for any of the at least one medical history record, the data processing module 704 is specifically configured to: acquiring current symptom information of the second user; identifying partial detailed data matched with the current symptom information of the second user in the detailed data corresponding to the medical history record by adopting a natural language processing algorithm; and sending the identification mark of the part of the detail data to the client so that the client can highlight the part of the detail data.

Fig. 8 is a schematic structural diagram of a client provided in an exemplary embodiment of the present application, where the client is applicable to the data processing system provided in the foregoing embodiment. As shown in fig. 8, the client includes: memory 801, processor 802, and communications component 803.

A memory 801 for storing computer programs and may be configured to store other various data to support operations on the server. Examples of such data include instructions for any application or method operating on the server, contact data, phonebook data, messages, pictures, videos, and so forth.

A processor 802, coupled to the memory 801, for executing computer programs in the memory 801 for: responding to the operation of inquiring the health data of a second user by a first user, and acquiring target health data of the second user from a server; displaying at least one basic information display area and at least one analysis result display area on a first page; in the at least one basic information display area, basic health data in the target health data are displayed in a classified mode, and in the at least one analysis result display area, health analysis results in the target health data are displayed in a classified mode.

Further optionally, the processor 802 is specifically configured to perform at least one of the following operations when the health analysis results in the target health data are displayed in the at least one analysis result display area in a classified manner: displaying at least one disease group and the corresponding number of times of treatment corresponding to the second user in the medical history overview area; displaying at least one health description label of the second user in a label display area; and displaying the health advice for the second user in an advice display area, wherein the health advice is generated according to the physical examination report data of the second user.

Further optionally, when the medical history overview region shows the at least one disease group and the corresponding number of visits corresponding to the second user, the processor 802 is further configured to: and responding to the selection operation of the target disease group in the at least one disease group, and displaying at least one disease type and the corresponding number of times of treatment under the target disease group in the medical history overview area.

Further optionally, when the processor 802 displays the basic health data in the target health data in the at least one basic information display area in a classified manner, specifically, the processor is configured to: acquiring a plurality of data categories contained in the basic health data; and displaying the view icons corresponding to the multiple data categories and the basic health data corresponding to the target data category in the multiple data categories in the medical history detail display area.

Further optionally, when the processor 802 displays the view icons corresponding to the multiple data categories and the basic health data corresponding to the target data category in the multiple data categories in the medical history detail display area, it is specifically configured to: acquiring at least one medical history record contained in the target data category; and displaying the at least one medical history record in a time shaft display form in the medical history detail display area according to the visit time sequence corresponding to the at least one medical history record.

Further optionally, the processor 802, when presenting the at least one medical history record in the presentation of a timeline, is further configured to: highlighting the medical history record with the relevance degree of the query intention of the first user being greater than or equal to a set threshold value, and folding and showing the medical history record with the relevance degree of the query intention of the first user being smaller than the set threshold value.

Further optionally, for any of the at least one medical history records, the processor 802 is further configured to: displaying a detail viewing icon corresponding to the medical history record in the medical history detail display area; responding to the triggering operation aiming at the detail viewing icon, and displaying a detail page of the medical history record; and displaying the detailed data corresponding to the medical history record in the form of text, picture, table and/or chart on the detailed page of the medical history record.

Further optionally, the processor 802 is further configured to: acquiring current symptom information of the second user; and highlighting part of the detail data matched with the current disease information of the second user in the detail data corresponding to the medical record in the detail page of the medical record.

Further optionally, the processor 802 is further configured to: acquiring the currently taken medicine of the second user; when the medicine taking time of the medicine is up, outputting a medicine taking reminding message; wherein, the taking time of the medicine is calculated according to the taking period and the taking times of the medicine.

Further optionally, the processor 802 is further configured to: displaying a screening icon in the query setting area so that the first user can input screening conditions of the health data; and/or, presenting an optional health data query time period in the query setting area for selection by the first user; and/or, displaying a query time self-defining control in the query setting area so as to enable the first user to define the query time period of the health data; and/or, a search component is presented in the query setting area for the first user to input search keywords for the health data.

Further, as shown in FIG. 8, the client may also include other components such as a display 804, a power component 805, and an audio component 806. Only some of the components are schematically shown in fig. 8, and the client is not meant to include only the components shown in fig. 8.

In this embodiment, when the first user initiates an operation of viewing the health data of the second user, the client may display the target health data in the health data of the second user, which is adapted to the query intention of the first user, so as to achieve multi-dimensional, multi-angle and flexible display of the health data, which is beneficial to assisting the first user to quickly know the health state of the second user, and improve the data query efficiency.

Accordingly, the present application further provides a computer-readable storage medium storing a computer program, where the computer program is capable of implementing the steps that can be executed by the client in the foregoing method embodiments when executed.

Fig. 9 is a schematic structural diagram of a server provided in an exemplary embodiment of the present application, where the server is applied to the data processing system provided in the foregoing embodiment. As shown in fig. 9, the server includes: memory 901, processor 902, and communications component 903.

A memory 901 for storing a computer program and may be configured to store other various data to support operations on the server. Examples of such data include instructions for any application or method operating on the server, contact data, phonebook data, messages, pictures, videos, and so forth.

A processor 902, coupled to the memory 901, for executing the computer program in the memory 901 for: receiving a data acquisition request through the communication component 903, where the data acquisition request is sent by a client when a first user queries health data of a second user; acquiring basic health data and health analysis results in the health data of the second user according to the data acquisition request, and taking the basic health data and the health analysis results as target health data; and sending the target health data to the client for displaying.

Further optionally, when the processor 902 acquires the basic health data in the health data of the second user according to the data acquisition request, specifically configured to: acquiring a department to which the first user belongs and at least one historical clinic department of the second user; respectively calculating the similarity between the department to which the first user belongs and the at least one historical clinic department; selecting a target historical clinic from the at least one historical clinic, wherein the similarity of the target historical clinic and the clinic to which the first user belongs is greater than a set similarity threshold; and acquiring medical data generated when the second user visits the target historical visiting department from the health data of the second user as the basic health data.

Further optionally, when the processor 902 calculates the similarity between the department to which the first user belongs and the at least one historical visiting department, it is specifically configured to: acquiring a code vector corresponding to the department to which the first user belongs according to the diagnosis code of the disease type contained in the department to which the first user belongs and tf-idf corresponding to the diagnosis code; acquiring coding vectors corresponding to the at least one historical clinic; and respectively calculating the similarity between the coding vector corresponding to the department to which the first user belongs and the coding vector corresponding to each of the at least one historical visiting department so as to obtain the similarity between the department to which the first user belongs and the at least one historical visiting department.

Further optionally, when obtaining the health analysis result in the health data of the second user, the processor 902 is specifically configured to: identifying health characteristics of the second user according to the health data of the second user; and generating at least one health description label of the second user as the health analysis result according to the health characteristics.

Further optionally, when obtaining the health analysis result in the health data of the second user, the processor 902 is specifically configured to: identifying at least one disease type of the second user's historical visits based on the second user's health data; dividing the at least one disease type into at least one disease group according to the disease group to which the disease type belongs; and taking the at least one disease group and the corresponding number of times of treatment as the health analysis result.

Further optionally, when obtaining the health analysis result in the health data of the second user, the processor 902 is specifically configured to: acquiring current symptom information of the second user; calculating at least one diagnosis suggestion for the second user according to the current symptom information of the second user and the health data corresponding to the second user, and sending the at least one diagnosis suggestion to the client for displaying; wherein the at least one visit recommendation comprises: at least one of an inquiry recommendation, an examination item recommendation, a medication intake recommendation, and a diagnosis and treatment recommendation associated with the second user.

Further optionally, when the processor 902 sends the target health data to the client for presentation, the processor is specifically configured to: classifying the basic health data to obtain a plurality of data classes; the plurality of data categories include: at least one of a syndrome category, a condition category, an examination category, an assay category, a treatment category, a surgery category, a drug category, an immunization category; and sending the multiple data types and the data corresponding to the multiple data types to the client for display.

Further optionally, the processor 902 is further configured to: acquiring historical viewing behaviors of the first user; analyzing the historical viewing behavior of the first user to obtain interest scores of the first user on the plurality of data categories; determining a data category with an interest score satisfying a set condition from the plurality of data categories as a target data category; an instruction to preferentially expose the target data category is sent to the client through the communication component 903.

Further optionally, the target data category comprises at least one medical history record; for any of the at least one medical history, the processor 902 is specifically configured to: acquiring current symptom information of the second user; identifying partial detailed data matched with the current symptom information of the second user in the detailed data corresponding to the medical history record by adopting a natural language processing algorithm; and sending the identification mark of the part of the detail data to the client so that the client can highlight the part of the detail data.

Further, as shown in fig. 9, the server further includes: power supply component 904, and the like. Only some of the components are schematically shown in fig. 9, and it is not meant that the server includes only the components shown in fig. 9.

In this embodiment, in the case of receiving the data acquisition request sent by the client, the basic health data and the health analysis result in the health data of the second user can be acquired according to the data acquisition request and serve as the target health data, and the target health data is displayed through the client, so that the multi-dimensional and multi-angle flexible display of the health data is realized, the first user is facilitated to quickly know the health state of the second user, and the data query efficiency is improved.

Accordingly, the present application further provides a computer-readable storage medium storing a computer program, where the computer program can implement the steps that can be executed by the server in the foregoing method embodiments when executed.

It should be noted that, the server shown in fig. 9 may also execute the steps in the method embodiments corresponding to fig. 5b, 5c, and 5d, which are not described herein again.

The memories of fig. 8 and 9 may be implemented by any type of volatile or non-volatile memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.

The communication components of fig. 8 and 9 described above are configured to facilitate communication between the device in which the communication component is located and other devices in a wired or wireless manner. The device in which the communication component is located may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component may be implemented based on Near Field Communication (NFC) technology, Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

The display in fig. 8 described above includes a screen, which may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

The power supply components of fig. 8 and 9 described above provide power to the various components of the device in which the power supply components are located. The power components may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device in which the power component is located.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A data processing method is suitable for a client, and is characterized by comprising the following steps:

responding to the operation of inquiring the health data of a second user by a first user, and acquiring target health data of the second user from a server;

displaying at least one basic information display area and at least one analysis result display area on a first page;

in the at least one basic information display area, basic health data in the target health data are displayed in a classified mode, and in the at least one analysis result display area, health analysis results in the target health data are displayed in a classified mode.

2. The method according to claim 1, wherein in the at least one analysis result display area, the health analysis results in the target health data are displayed in a classified manner, and the method comprises at least one of the following steps:

displaying at least one disease group and the corresponding number of times of treatment corresponding to the second user in a medical history overview region;

displaying at least one health description label of the second user in a label display area;

and displaying health suggestions for the second user in a suggestion display area, wherein the health suggestions are generated according to physical examination report data of the second user.

3. The method of claim 2, wherein displaying the at least one disease grouping and the number of visits corresponding to the second user in a medical history overview area further comprises:

and responding to the selection operation of the target disease group in the at least one disease group, and displaying at least one disease type and the corresponding number of times of treatment under the target disease group in the medical history overview area.

4. The method according to claim 1, wherein the classifying and displaying of the basic health data in the target health data in the at least one basic information displaying area comprises:

acquiring a plurality of data categories contained in the basic health data;

and displaying the view icons corresponding to the multiple data categories and the basic health data corresponding to the target data category in the multiple data categories in a medical history detail display area.

5. The method according to claim 4, wherein displaying, in the medical history detail display area, the view icons corresponding to the plurality of data categories and the basic health data corresponding to the target data category in the plurality of data categories comprises:

acquiring at least one medical history record contained in the target data category;

and displaying the at least one medical history record in a time shaft display form in the medical history detail display area according to the visit time sequence corresponding to the at least one medical history record.

6. The method of claim 5, wherein presenting the at least one medical history record in an presentation of a timeline further comprises:

highlighting the medical history record with the relevance degree of the query intention of the first user being greater than or equal to a set threshold value, and folding and displaying the medical history record with the relevance degree of the query intention of the first user being smaller than the set threshold value.

7. The method of claim 5, further comprising, for any of the at least one medical history record:

displaying a detail viewing icon corresponding to the medical history record in the medical history detail display area;

responding to the triggering operation aiming at the detail viewing icon, and displaying a detail page of the medical history record;

and displaying the detailed data corresponding to the medical history record in the form of text, picture, table and/or chart on the detailed page of the medical history record.

8. The method of claim 7, further comprising:

acquiring current symptom information of the second user;

and highlighting part of detail data matched with the current disease information of the second user in the detail data corresponding to the medical record in the detail page of the medical record.

9. The method of any one of claims 4-8, wherein the target health data comprises a plurality of data categories including: at least one of a syndrome category, a condition category, an examination category, an assay category, a treatment category, a surgery category, a drug category, an immunization category.

10. The method according to any one of claims 1-8, further comprising:

acquiring a medicine currently taken by the second user;

outputting a medicine taking reminding message when the medicine taking time of the medicine is reached;

wherein the taking time of the medicine is calculated according to the taking period and the taking times of the medicine.

11. The method according to any one of claims 1-8, further comprising:

displaying a screening icon in a query setting area so that the first user can input screening conditions of the health data; and/or the presence of a gas in the gas,

displaying an optional health data query time period in the query setting area for the first user to select; and/or the presence of a gas in the gas,

displaying a query time self-defining control in the query setting area so as to enable the first user to define the query time period of the health data; and/or the presence of a gas in the gas,

and displaying a search component in the query setting area so that the first user can input search keywords aiming at the health data.

12. A data processing method is suitable for a server, and is characterized by comprising the following steps:

receiving a data acquisition request, wherein the data acquisition request is sent by a client when a first user inquires health data of a second user;

acquiring basic health data and health analysis results in the health data of the second user according to the data acquisition request, and taking the basic health data and the health analysis results as target health data;

and sending the target health data to the client for display.

13. The method of claim 12, wherein obtaining the underlying health data in the health data of the second user according to the data obtaining request comprises:

acquiring a department to which the first user belongs and at least one historical clinic department of the second user;

respectively calculating the similarity of the department to which the first user belongs and the at least one historical clinic department;

selecting a target historical clinic from the at least one historical clinic, wherein the similarity of the target historical clinic and the clinic to which the first user belongs is greater than a set similarity threshold;

and acquiring medical data generated when the second user visits the target historical visiting department from the health data of the second user as the basic health data.

14. The method of claim 13, wherein calculating the similarity of the department to which the first user is affiliated and the at least one historical visit department, respectively, comprises:

acquiring a code vector corresponding to the department to which the first user belongs according to the diagnosis code of the disease type contained in the department to which the first user belongs and tf-idf corresponding to the diagnosis code;

acquiring a coding vector corresponding to each of the at least one historical clinic;

and respectively calculating the similarity between the coding vector corresponding to the department to which the first user belongs and the coding vector corresponding to each of the at least one historical visiting department so as to obtain the similarity between the department to which the first user belongs and the at least one historical visiting department.

15. The method of claim 12, wherein obtaining the health analysis results in the health data of the second user comprises:

identifying health characteristics of the second user according to the health data of the second user;

and generating at least one health description label of the second user as the health analysis result according to the health characteristics.

16. The method of claim 15, wherein the health characteristics comprise: one or more of a visit behavior characteristic, a treatment means characteristic, a physical state characteristic, and a life habit characteristic.

17. The method of claim 12, wherein obtaining the health analysis results in the health data of the second user comprises:

identifying at least one disease type of the second user's historical encounter based on the second user's health data;

dividing the at least one disease type into at least one disease group according to the disease group to which the disease type belongs;

and grouping the at least one disease and the corresponding number of times of treatment as the health analysis result.

18. The method of claim 12, wherein obtaining the health analysis results in the health data of the second user comprises:

acquiring current symptom information of the second user;

calculating at least one diagnosis suggestion for the second user according to the current symptom information of the second user and the health data corresponding to the second user, and sending the at least one diagnosis suggestion to the client for displaying;

wherein the at least one visit recommendation comprises: at least one of an inquiry recommendation, an examination item recommendation, a medication intake recommendation, and a diagnosis and treatment recommendation associated with the second user.

19. The method of any one of claims 12-18, wherein sending the target health data to the client for presentation comprises:

classifying the basic health data to obtain a plurality of data categories; the plurality of data categories include: at least one of a syndrome category, a condition category, an examination category, an assay category, a treatment category, a surgery category, a drug category, an immunization category;

and sending the multiple data types and the data corresponding to the multiple data types to the client for displaying.

20. The method of claim 19, further comprising:

acquiring historical viewing behaviors of the first user;

analyzing the historical viewing behavior of the first user to obtain interest scores of the first user for the plurality of data categories;

determining a data category with an interest score meeting a set condition from the plurality of data categories as a target data category;

and sending an instruction for preferentially displaying the target data category to the client.

21. The method of claim 20, wherein the target data category comprises at least one medical history record; for any of the at least one medical history, the method further comprises:

acquiring current symptom information of the second user;

identifying partial detailed data matched with the current symptom information of the second user in the detailed data corresponding to the medical history record by adopting a natural language processing algorithm;

and sending the identification mark of the partial detail data to the client so that the client can highlight the partial detail data.

22. A data processing method is suitable for a server, and is characterized by comprising the following steps:

receiving a data acquisition request, wherein the data acquisition request is sent by a client when a first user inquires health data of a second user, and the data acquisition request carries identity information of the first user;

if the first user is identified as a medical subsidy processing user according to the identity information of the first user, acquiring diagnosis and treatment records and diagnosis and treatment expense data corresponding to the target disease type meeting the medical subsidy condition from the health data of the second user;

and sending the diagnosis and treatment records and the diagnosis and treatment expense data corresponding to the target disease type to a client for displaying so as to be checked by the first user.

23. A data processing method is suitable for a server, and is characterized by comprising the following steps:

if the first user is identified as a commercial insurance processing user according to the identity information of the first user, sending an authorization request to the second user according to the identity information of the first user;

if receiving an authorization notification message returned by the second user according to the authorization request, acquiring health data associated with commercial insurance from the health data of the second user;

and sending the health data associated with the commercial insurance to a client for displaying so as to be viewed by the first user.

24. The method of claim 23, wherein the health data associated with the commercial insurance comprises: the health data of the second user when the second user is in insurance application, the health data of the second user when the second user continues to be in insurance application, or the health data of the second user when applying for insurance claims.

25. A data processing method, comprising:

receiving a data acquisition request, wherein the data acquisition request is sent by a client when a first user inquires health data, and the data acquisition request carries identity information of the first user;

if the first user is identified as a disease control user in a set geographical range according to the identity information of the first user, acquiring medical data of a plurality of medical institutions in the set geographical range;

calculating the disease distribution characteristics in the set region range according to the medical data;

and sending the disease distribution characteristics to a client for displaying so as to be viewed by the first user.

26. The method of claim 25, wherein the disease distribution profile includes at least one of: frequency of visits for each disease, period of visits for each disease, medical institution of visits for each disease, age of onset for each disease.

27. The method of claim 25, further comprising:

according to the disease distribution characteristics, calculating the target diseases with the frequency of treatment greater than a set frequency threshold;

outputting an early warning message for the target disease.

28. A health data display apparatus, comprising:

the acquisition module is used for responding to the operation of inquiring the health data of a second user by a first user and acquiring the target health data of the second user from a server;

the display module is used for displaying at least one basic information display area and at least one analysis result display area on a first page; in the at least one basic information display area, basic health data in the target health data are displayed in a classified mode, and in the at least one analysis result display area, health analysis results in the target health data are displayed in a classified mode.

29. A health data display apparatus, comprising:

the system comprises a receiving module, a sending module and a receiving module, wherein the receiving module is used for receiving a data acquisition request, and the data acquisition request is sent by a client when a first user inquires health data of a second user;

the data acquisition module is used for acquiring basic health data and health analysis results in the health data of the second user according to the data acquisition request, and the basic health data and the health analysis results are used as target health data;

and the sending module is used for sending the target health data to the client for displaying.

30. A client, comprising: a memory, a processor, and a communications component;

the memory is to store one or more computer instructions;

the processor is to execute the one or more computer instructions to: performing the steps in the data processing method of any one of claims 1-11.

31. A server, comprising: a memory, a processor, and a communications component;

the memory is to store one or more computer instructions;

the processor is to execute the one or more computer instructions to: performing the steps in the data processing method of any one of claims 12 to 27.

32. A computer-readable storage medium storing a computer program, wherein the computer program is capable of implementing the steps in the data processing method of any one of claims 1 to 27 when executed.

33. A data processing system, comprising: a client and a server;

wherein the client is configured to: according to the operation of a first user for inquiring the health data of a second user, acquiring target health data of the second user from the server, displaying basic health data in the target health data in a classified mode, and displaying health analysis results in the target health data in a classified mode;

the server is configured to: and when the data acquisition request is received, acquiring basic health data and health analysis results in the health data of the second user as target health data, and sending the target health data to the client.