CN108766512B - Health data management method and device, computer equipment and storage medium - Google Patents
Health data management method and device, computer equipment and storage medium Download PDFInfo
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- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
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- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
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Abstract
The application relates to a health data management method, a health data management device, a computer device and a storage medium. The method comprises the following steps: acquiring registration data, behavior data and medical data corresponding to a plurality of user identifications; calculating user characteristics corresponding to the user identification according to the registration data, the behavior data and the medical data; acquiring a plurality of service items, and extracting corresponding service keywords according to the service items; matching the user characteristics with the service keywords to obtain a plurality of recommended service items; and generating prompt information of health management by using the plurality of recommended service items, and sending the prompt information to a terminal corresponding to the user identification. According to the method, the user characteristics corresponding to the user identification are calculated, comprehensive data related to the user can be obtained, the prompt information of health management is generated according to the recommended service item, and the prompt information is sent to the corresponding terminal. Therefore, the most suitable service items can be recommended to each user, and therefore comprehensive and personalized health management of the user is achieved.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for managing health data, a computer device, and a storage medium.
Background
With the development of society, the pace of life of people is accelerated and the working pressure is increased, so that a series of health problems are brought, and people pay more and more attention to their health conditions, so that various health management software including sports software, recipe software and the like appears. The exercise software can provide a healthy exercise mode according to personal data of the user, such as height, weight, age and the like, and the recipe software can provide healthy diet standards and a three-meal recipe according to the eating habits or physical qualities of the user.
However, directions related to each product on the market are relatively independent, when people use the health management software, health management in the corresponding direction can be executed only according to contents provided by the software, and the health management scheme provided by the health product cannot provide a comprehensive and reliable health management scheme for different user groups because only part of data of users is collected.
Disclosure of Invention
In view of the above, there is a need to provide a health data management method, apparatus, computer device and storage medium capable of providing a comprehensive health management solution for different users.
A method of health data management, the method comprising:
acquiring registration data, behavior data and medical data corresponding to a plurality of user identifications;
calculating user characteristics corresponding to the user identification according to the registration data, the behavior data and the medical data;
acquiring a plurality of service items, and extracting corresponding service keywords according to the service items;
matching the user characteristics with the service keywords to obtain a plurality of recommended service items;
and generating prompt information of health management by using a plurality of recommended service items, and sending the prompt information to a terminal corresponding to the user identifier.
In one embodiment, the behavioral data includes a motion field and the medical data includes a medical field; the method further comprises the following steps:
acquiring a plurality of preset motion fields and medical fields, and generating an SQL statement by using the motion fields and the medical fields;
respectively reading corresponding motion data and/or medical data in a plurality of source databases through the SQL sentence;
and writing the read motion data and/or medical data into a target database.
In one embodiment, the calculating the user characteristic corresponding to the user identifier according to the registration data, the behavior data and the medical data includes:
calculating a behavior track corresponding to the user identification according to the behavior data;
generating a health record corresponding to the user identification according to the medical data;
analyzing a user portrait corresponding to the user identification according to the registration data, the behavior track and the health file;
and extracting the user characteristics corresponding to the user identification according to the user portrait.
In one embodiment, the method further comprises:
classifying a plurality of user identifications according to the user characteristics, and adding category labels to the user identifications;
and acquiring corresponding push messages according to the category labels, and sending the push messages corresponding to the category labels to terminals corresponding to a plurality of user identifications.
In one embodiment, the method further comprises:
presetting a data acquisition period, and acquiring behavior data and medical data in different data acquisition period segments;
calculating user characteristics in different data acquisition periods according to the registration data, the behavior data in different data acquisition period segments and the medical data;
matching the user characteristics with the service keywords to obtain a plurality of recommended service items in different data acquisition periods;
and generating prompt information of health management by using the plurality of recommended service items, and sending the prompt information to a terminal corresponding to the user identification.
A health data management apparatus, the apparatus comprising:
the data acquisition module is used for acquiring registration data, behavior data and medical data corresponding to the user identifications;
the characteristic calculation module is used for calculating user characteristics corresponding to the user identification according to the registration data, the behavior data and the medical data;
the matching module is used for acquiring a plurality of service items and extracting corresponding service keywords according to the service items; matching the user characteristics with the service keywords to obtain a plurality of recommended service items;
and the sending module is used for generating prompt information of health management by using the plurality of recommended service items and sending the prompt information to the terminal corresponding to the user identifier.
In one embodiment, the apparatus further comprises:
the system comprises a synchronization module, a query module and a query module, wherein the synchronization module is used for acquiring a plurality of preset motion fields and medical fields and generating an SQL statement by using the motion fields and the medical fields; respectively reading corresponding motion data and/or medical data in a plurality of source databases through the SQL sentences; and writing the read motion data and/or medical data into a target database.
In one embodiment, the apparatus further comprises:
the classification module is used for classifying a plurality of user identifications according to the user characteristics and adding class labels to the user identifications;
the sending module is further configured to obtain a corresponding push message according to the category label, and send the push message corresponding to the category label to terminals corresponding to multiple user identifiers.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring registration data, behavior data and medical data corresponding to a plurality of user identifications;
calculating user characteristics corresponding to the user identification according to the registration data, the behavior data and the medical data;
acquiring a plurality of service items, and extracting corresponding service keywords according to the service items;
matching the user characteristics with the service keywords to obtain a plurality of recommended service items;
and generating prompt information of health management by using a plurality of recommended service items, and sending the prompt information to a terminal corresponding to the user identifier.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring registration data, behavior data and medical data corresponding to a plurality of user identifications;
calculating user characteristics corresponding to the user identification according to the registration data, the behavior data and the medical data;
acquiring a plurality of service items, and extracting corresponding service keywords according to the service items;
matching the user characteristics with the service keywords to obtain a plurality of recommended service items;
and generating prompt information of health management by using a plurality of recommended service items, and sending the prompt information to a terminal corresponding to the user identifier.
According to the health data management method, the health data management device, the computer equipment and the storage medium, the registration data, the behavior data and the medical data corresponding to the user identification are obtained, the user characteristics corresponding to the user identification are calculated according to the obtained data, comprehensive data related to the user are obtained, the service keywords of the obtained service items are matched with the user characteristics, a plurality of recommended service items are obtained, the prompt information of health management is generated according to the recommended service items, and the prompt information is sent to the terminal corresponding to the user identification. Therefore, the most suitable service items can be recommended to each user, and therefore comprehensive and personalized health management of the user is achieved.
Drawings
FIG. 1 is a diagram illustrating an exemplary embodiment of a health data management method;
FIG. 2 is a flow diagram illustrating a method for health data management in one embodiment;
FIG. 3 is a schematic flow chart illustrating steps for calculating user characteristics corresponding to a user identifier based on enrollment data, behavioral data, and medical data in one embodiment;
FIG. 4 is a flowchart showing the steps of answering a user question in another embodiment;
FIG. 5 is a block diagram showing the configuration of a health data management apparatus according to an embodiment;
FIG. 6 is a block diagram showing the structure of a health data management apparatus according to another embodiment;
FIG. 7 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The health data management method provided by the application can be applied to the application environment shown in fig. 1. The terminal 102 communicates with the server 104 through a network, the server 104 obtains registration data, behavior data and medical data corresponding to a plurality of user identifiers from the terminal 102, calculates user characteristics corresponding to the user identifiers according to the obtained registration data, behavior data and medical data, obtains a plurality of service items from a database, extracts corresponding service keywords according to the service items, matches the obtained user characteristics with the service keywords to obtain a plurality of recommended service items, generates prompt information for health management according to the plurality of recommended service items, and sends the prompt information to the terminal 102 corresponding to the user identifiers. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server 104 may be implemented by an independent server or a server cluster formed by a plurality of servers.
In one embodiment, as shown in fig. 2, a health data management method is provided, which is described by taking the method as an example applied to the server in fig. 1, and includes the following steps:
s202, acquiring registration data, behavior data and medical data corresponding to a plurality of user identifications.
The registration data refers to data input by the user during registration, and includes basic information such as a user name, the user age and the gender.
The behavior data comprises all user behavior data, such as browsing records, purchasing records, service performance records and the like, wherein the browsing records represent browsing records of service items of the user, the browsable service items comprise information, medical services, health products and the like, the purchasing records represent purchasing records of the service items of the user, the purchasable service items comprise purchases of health products, fitness courses and the like, and the service performance comprises performance of the purchased or selected service items of the user.
The medical data includes data of blood sugar, blood pressure, diagnosis result, case and the like of the user, and can be acquired through a third-party platform or information input by the user.
Specifically, the information includes health information, diet instructions and daily work and rest about health, medical information, such as symptoms of a disease or medication for solving a disease.
The medical services comprise traditional Chinese medicine constitution conditioning, can be used for improving the constitution of a user and preventing diseases, and also comprise rehabilitation guidance, medication reminding, traditional Chinese medicine therapy and the like, and can respectively provide rehabilitation guidance for the user suffering from the diseases, provide corresponding medication reminding for the user suffering from the diseases, provide traditional Chinese medicine therapy different from the existing western medicine therapy and the like.
The health products comprise various health products, slimming products and the like, and the fitness courses comprise courses for fitness and slimming.
The service fulfillment comprises the operation of a user after selecting the corresponding service, whether the user learns according to the selected service, such as a fitness course, if the user does not learn according to the selected course, the server sends other related courses to the client, when the user learns according to the selected course, the server records the learning time point and the learning time length of the user course, sets corresponding reminding, and when the reminding time is up, the server sends reminding information to the user.
And acquiring medical data related to the user through the third-party platform or information input by the user, wherein the medical data comprises results of blood sugar, blood pressure, diagnosis results, cases and the like of the user. The server obtains the information input by the user, and can send a questionnaire to the user or obtain the information input by the user actively inquiring.
And S204, calculating the user characteristics corresponding to the user identification according to the registration data, the behavior data and the medical data.
Wherein, the user characteristic is a characteristic mark obtained by calculating the user portrait. The user portrait refers to a tagged user model abstracted according to social attributes, living habits and consumption behaviors, the core work of constructing the user portrait is to add tags to users, and the tags are feature identifications obtained through analyzing user information, namely user features. Specifically, the server obtains the user characteristics corresponding to the user identifier by performing calculation according to the registration data, the behavior data and the medical data of the user.
Furthermore, the registration data of the user belongs to static data, the behavior data and the medical data of the user belong to dynamic data, and the behavior data and the medical data of the user are updated in different periods.
S206, acquiring a plurality of service items, and extracting corresponding service keywords according to the service items.
The service items comprise various services, such as pushing health information and medical information, recommending health products and slimming products, providing fitness courses and slimming courses, providing traditional Chinese medicine treatment and traditional Chinese medicine physique conditioning, establishing health files of users and the like.
Specifically, different service items have different service keywords, and the service keywords corresponding to the service items can be extracted according to the service items, for example, when the service items are pushing health information or medical information, the corresponding service keywords are information; when the service item is a recommended health-care product or a slimming product, the corresponding service keyword is a health product; when the service items are fitness course and slimming course, the corresponding service keywords are health courses; when the service item is to establish the health file of the user, the corresponding service keyword is the health file.
Furthermore, an update cycle is preset for different service items, and in different update cycle segments, different service items, including recipes, drug dosage, fitness courses and the like, are adjusted correspondingly along with the updating of the behavior data and the medical data of the user so as to be matched with the updated user characteristics.
And S208, matching the user characteristics with the service keywords to obtain a plurality of recommended service items.
And calculating the similarity between the user characteristics and the service keywords to obtain the matching relationship between the user characteristics and the service keywords. In this embodiment, the server may calculate similarity values between the user features and the service keywords according to a similarity algorithm, determine a matching relationship between the user features and the service keywords according to the similarity values, and recommend the user according to the degree of the matching relationship. The first n service items with high matching degree can be selected and recommended to the user, and n is a value not exceeding the number of the service items.
And S210, generating prompt information of health management by using the plurality of recommended service items, and sending the prompt information to a terminal corresponding to the user identifier.
And producing prompt information of health management according to the service recommendation items, including the service items recommended to the user, prompt messages and the like.
The service items recommended to the user comprise pushing health information and medical information, recommending health care products and slimming products, providing fitness courses and slimming courses, providing traditional Chinese medicine treatment and traditional Chinese medicine constitution conditioning, establishing health files of the user and the like, and the reminding message can be sent according to the performance condition of the user and can be generated according to the health courses selected by the user, the purchased health products and the like.
And sending prompt information generated according to the recommended service items to a terminal corresponding to the user identifier, wherein the terminal can include but is not limited to various personal computers, notebook computers, smart phones, tablet computers and portable wearable devices.
Furthermore, the terminals corresponding to different user identifiers can receive the prompt information of health management sent by the server and acquire the recommended service items included in the prompt information.
The method comprises the steps that a user can send feedback information to a server according to the treatment condition of a currently recommended service item, if the effect is not good, a request for adjusting, replacing or optimizing the service item can be sent to the server, when the server receives the feedback information sent by the user and the request for adjusting, replacing or optimizing the service item, real-time behavior data and medical data of the user and the feedback information and the request of the user are obtained, user characteristics are generated, matching operation is executed according to service keywords, an updated recommended service item is obtained, prompt information of health management is generated according to the recommended service item, and the prompt information is sent to a terminal corresponding to a user identifier.
According to the health data management method, registration data, behavior data and medical data corresponding to user identification are obtained, user characteristics corresponding to the user identification are calculated according to the obtained data, comprehensive data related to a user are obtained, service keywords of the obtained service items are matched with the user characteristics, a plurality of recommended service items are obtained, prompt information of health management is generated according to the recommended service items, and the prompt information is sent to a terminal corresponding to the user identification. Therefore, the most suitable service items can be recommended to each user, and therefore comprehensive and personalized health management of the user is achieved.
In one embodiment, a plurality of preset motion fields and medical fields are obtained, and SQL sentences are generated by utilizing the motion fields and the medical fields; respectively reading corresponding motion data and/or medical data in a plurality of source databases through SQL statements; and writing the read motion data and/or medical data into a target database.
In this embodiment, the behavior data includes a motion field and the medical data includes a medical field. The exercise field refers to key words extracted from a plurality of exercise types related to the health class, including aerobic exercises and anaerobic exercises, wherein the aerobic exercises include jogging, yoga gymnastics, dancing and the like, and the anaerobic exercises include exercises for various instruments, weight lifting instruments, gymnastics instruments, strength training instruments and the like. The medical field refers to key words extracted from data such as blood glucose, blood pressure, diagnosis results, and cases of the user.
The source database may be one or more. The source database and the target database may be respectively deployed on the same server, or may be deployed on different servers. The source database and the target database can be relational databases, such as a Sql Server database, an Oracle database or a MySql database and the like; but may also be a non-relational database, etc.
The method comprises the steps that a terminal obtains preset keywords, generates corresponding SQL sentences according to the keywords, reads corresponding motion data and/or medical data in a plurality of source databases respectively by utilizing the SQL sentences, extracts the motion data and/or the medical data related to the keywords from the source databases respectively, and writes the read motion data and/or medical data into a target database.
In the above embodiment, the motion data and/or the medical data in the multiple source databases are read and synchronized to the local target database, so that convenience is provided for acquiring the behavior data and the medical data.
In one embodiment, as shown in fig. 3, there is provided a step of calculating a user characteristic corresponding to a user identification from the registration data, the behavior data and the medical data, comprising:
and S302, calculating a behavior track corresponding to the user identification according to the behavior data.
The behavior data comprises all user behavior data including browsing record, purchasing record, service fulfillment record and the like, and according to the behavior data of the user, user behavior tracks corresponding to the user behavior data can be calculated and obtained, including browsing tracks, purchasing tracks, service fulfillment tracks and the like.
Specifically, the server acquires behavior data of the user, and divides the behavior data of the user into browsing records, purchasing records and service performance records according to various behavior keywords in the behavior data.
Furthermore, the server acquires the service items browsed in the browsing record, the related information of each browsed service item and the frequency of the browsed service items, and calculates the browsing track of the user according to the acquired information.
The server acquires the service items purchased in the purchase record, the related information of each purchased service item and the frequency of the purchased service items, and calculates the purchase track of the user according to the acquired information of the purchase record.
The server acquires the service items selected or purchased by the user and the performance of the selected or purchased service items in the service performance record, divides the acquired performance into user performance or user non-performance, and calculates the service performance track of the user according to the performance and non-performance of the user.
And S304, generating a health record corresponding to the user identifier according to the medical data.
The medical data includes data such as blood sugar, blood pressure, diagnosis result and case of the user, and the medical data of the user can be acquired from a third-party platform or according to information input by the user.
The server establishes a corresponding health file for each user according to the acquired data such as blood sugar, blood pressure, diagnosis results, cases and the like.
The health record includes life habit, past medical history, diagnosis and treatment condition, family medical history, present medical history, physical examination result, disease occurrence, development, treatment and outcome process, and records of all vital signs of the user and all health related actions and events.
S306, analyzing the user portrait corresponding to the user identification according to the registration data, the behavior track and the health file.
And S308, extracting the user characteristics corresponding to the user identification according to the user portrait.
Specifically, the server abstracts the tagged user model according to the social attributes, living habits, consumption behaviors and the like of the user, and adds tags to the user according to the user model, wherein the tags are feature identifications obtained by analyzing information of the user, namely user features. User features corresponding to the user identification can be extracted from the obtained user portrait.
In this embodiment, the user profile corresponding to the user identifier is analyzed according to the registration data, the behavior trajectory and the health profile of the user, and the user characteristics are extracted, wherein the user characteristics are obtained from the registration data, the behavior trajectory of the user and the health profile established by using the medical data of the user, and the accuracy of the extracted user characteristics is improved.
In one embodiment, a health data management method is provided, the method further comprising:
classifying a plurality of user identifications according to the user characteristics, and adding category labels to the user identifications; and acquiring corresponding push messages according to the category labels, and sending the push messages corresponding to the category labels to terminals corresponding to the plurality of user identifications.
Specifically, a corresponding relationship among the user characteristics, the user identifiers and the user category labels is first established, where different user identifiers correspond to different user characteristics, or one user identifier corresponds to multiple user characteristics, that is, the category labels correspond to the user characteristics, and different user characteristics correspond to different category labels, and similarly, one user identifier may also correspond to multiple category labels.
The server can acquire the category label corresponding to the user identifier and send the push message corresponding to the category label to the terminals corresponding to the user identifiers according to the corresponding relationship between the category label and the push desired message.
In this embodiment, category labels are added to different user identifiers, and push messages corresponding to the category labels are pushed to terminals corresponding to the user identifiers, so that a function of pushing different messages for different users can be realized, and personalized services can be realized.
In one embodiment, as shown in fig. 4, there is provided a health data management method, further comprising:
s402, presetting a data acquisition period, and acquiring behavior data and medical data in different data acquisition period segments.
The behavior data and the medical data of the user belong to dynamic data and are updated in real time, the registration data of the user belong to static data, and the recommended service items are adjusted according to user characteristics formed by the static data and the dynamic data in different period segments.
Specifically, the data acquisition period is a time interval at which the server acquires dynamic data of the user, that is, different time periods during which behavior data and medical data of the user are acquired, and the server periodically acquires the behavior data and the medical data of the user according to the set data acquisition period.
S404, calculating to obtain user characteristics in different data acquisition periods according to the registration data, the behavior data in different data acquisition period segments and the medical data.
The user characteristics are characteristic marks obtained by calculating the user portrait. The user portrait refers to a tagged user model abstracted according to social attributes, living habits and consumption behaviors, the core work of constructing the user portrait is to add tags to users, and the tags are feature identifications obtained through analyzing user information, namely user features.
Specifically, the registration data of the user belongs to static data, the behavior data and the medical data of the user belong to dynamic data, the behavior data and the medical data of the user can be updated in different period sections, and the server acquires the behavior data and the medical data in different period sections and calculates the user characteristics corresponding to the user identification in real time by combining the registration data.
S406, matching the user characteristics with the service keywords to obtain a plurality of recommended service items in different data acquisition periods.
The service items comprise various services, such as pushing health information and medical information, recommending health products and slimming products, providing fitness courses and slimming courses, providing traditional Chinese medicine treatment and traditional Chinese medicine physique conditioning, establishing health files of users and the like. Different service items have different service keywords, and the service keywords corresponding to the service items can be extracted according to the service items.
In this embodiment, the server may calculate similarity values between the user features and the service keywords according to a similarity algorithm, determine a matching relationship between the user features and the service keywords according to the similarity values, and recommend the user according to the degree of the matching relationship.
Furthermore, an update cycle is preset for different service items, and in different update cycle segments, different service items, including recipes, drug dosage, fitness courses and the like, are adjusted correspondingly along with the updating of the behavior data and the medical data of the user so as to be matched with the updated user characteristics.
And S408, generating prompt information of health management by using the plurality of recommended service items, and sending the prompt information to a terminal corresponding to the user identifier.
The method comprises the steps of obtaining a plurality of recommended service items according to the matching relation between user characteristics and service keywords, and producing prompt information of health management according to the service recommended items, wherein the prompt information comprises the service items recommended to users, prompt messages and the like.
Specifically, the service items recommended to the user include pushing health information and medical information, recommending health care products and slimming products, providing fitness courses and slimming courses, providing traditional Chinese medicine therapy and traditional Chinese medicine physique conditioning, establishing health files of the user, and the like, and the reminding message can be sent according to the performance conditions of the user, and can be generated according to the health courses selected by the user, the purchased health products, and the like.
According to the health data management method, the data acquisition period is set, the behavior data and the medical data of the user are acquired in different period segments, the user characteristics in different period segments are generated in real time by combining the registration data, the matching is carried out according to the user characteristics and the service keywords, the recommended service items in different period segments can be acquired, real-time service is provided for the user, meanwhile, the user can send feedback information and a request for adjusting, replacing or optimizing the service items to the server, the server can re-recommend the service items for the user after receiving the feedback information or the request of the user, and flexible personalized service management is achieved.
It should be understood that although the various steps in the flow charts of fig. 2-4 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-4 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 5, there is provided a health data management apparatus including:
the data acquiring module 502 is configured to acquire registration data, behavior data, and medical data corresponding to a plurality of user identifiers.
The registration data refers to data input by the user during registration, and includes basic information such as a user name, the user age and the gender.
The behavior data includes all user behavior data, such as browsing records, purchasing records, service performance records, and the like, wherein the browsable service items include information, medical services, health products, and the like, the purchasing can include purchasing health products, fitness courses, and the like, and the service performance includes the performance of the purchased or selected service by the user.
The medical data includes data of blood sugar, blood pressure, diagnosis result, case and the like of the user, and can be acquired through a third-party platform or information input by the user.
And the feature calculation module 504 is configured to calculate a user feature corresponding to the user identifier according to the registration data, the behavior data, and the medical data.
Wherein, the user characteristic is a characteristic mark obtained by calculating the user portrait. The user portrait refers to a tagged user model abstracted according to social attributes, living habits and consumption behaviors, the core work of constructing the user portrait is to add tags to users, and the tags are feature identifications obtained through analyzing user information, namely user features.
Specifically, according to the application, the user characteristics corresponding to the user identification are obtained by calculating according to the registration data, the behavior data and the medical data of the user.
The matching module 506 is used for acquiring a plurality of service items and extracting corresponding service keywords according to the service items; and matching the user characteristics with the service keywords to obtain a plurality of recommended service items.
The service items comprise various services, such as pushing health information and medical information, recommending health products and slimming products, providing fitness courses and slimming courses, providing traditional Chinese medicine treatment and traditional Chinese medicine physique conditioning, establishing health files of users and the like.
Specifically, the matching relationship between the user characteristics and the service keywords is obtained by calculating the similarity between the user characteristics and the service keywords. In the embodiment, the similarity value between the user characteristic and each service keyword can be calculated according to a similarity algorithm, the matching relationship between the user characteristic and each service keyword is judged according to the similarity value, and the recommendation to the user is carried out according to the degree of the matching relationship.
A sending module 508, configured to generate prompt information for health management by using the plurality of recommended service items, and send the prompt information to a terminal corresponding to the user identifier.
And producing prompt information of health management according to the service recommendation items, including the service items recommended to the user, prompt messages and the like.
According to the health data management device, the registration data, the behavior data and the medical data corresponding to the user identification are obtained, the user characteristics corresponding to the user identification are calculated according to the obtained data, comprehensive data related to the user are obtained, the service keywords of the obtained service items are matched with the user characteristics, a plurality of recommended service items are obtained, the prompt information of health management is generated according to the recommended service items, and the prompt information is sent to the terminal corresponding to the user identification. Therefore, the most suitable service items can be recommended to each user, and therefore comprehensive and personalized health management of the user is achieved.
In one embodiment, the health data management apparatus further comprises:
the system comprises a synchronization module, a query module and a query module, wherein the synchronization module is used for acquiring a plurality of preset motion fields and medical fields and generating an SQL statement by using the motion fields and the medical fields; respectively reading corresponding motion data and/or medical data in a plurality of source databases through the SQL sentences; and writing the read motion data and/or medical data into a target database.
In this embodiment, the behavior data includes a motion field and the medical data includes a medical field. The exercise field refers to key words extracted from a plurality of exercise types related to the health class, including aerobic exercises and anaerobic exercises, wherein the aerobic exercises include jogging, yoga gymnastics, dancing and the like, and the anaerobic exercises include exercises for various instruments, weight lifting instruments, gymnastics instruments, strength training instruments and the like. The medical field refers to key words extracted from data such as blood glucose, blood pressure, diagnosis results, and cases of the user.
The source database may be one or more. The source database and the target database may be respectively deployed on the same server, or may be deployed on different servers. The source database and the target database can be relational databases, such as Sql Server database, oracle database or MySql database; but may also be a non-relational database, etc.
The method comprises the steps that a terminal obtains preset keywords, generates corresponding SQL sentences according to the keywords, reads corresponding motion data and/or medical data in a plurality of source databases respectively by utilizing the SQL sentences, extracts the motion data and/or the medical data related to the keywords from the source databases respectively, and writes the read motion data and/or medical data into a target database.
In the above embodiment, the motion data and/or the medical data in the multiple source databases are read and synchronized to the local target database, so that convenience is provided for acquiring the behavior data and the medical data.
In one embodiment, the user characteristic calculation module comprises:
and the behavior track calculation unit is used for calculating a behavior track corresponding to the user identification according to the behavior data.
The behavior data comprises all user behavior data including browsing records, purchasing records, service fulfillment records and the like, and according to the behavior data of the user, a user behavior track corresponding to the user behavior data can be calculated and obtained, wherein the user behavior track includes browsing, purchasing, service fulfillment records and the like.
And the health record establishing unit is used for generating a health record corresponding to the user identifier according to the medical data.
The medical data includes data such as blood sugar, blood pressure, diagnosis result and case of the user, and the medical data of the user can be acquired from a third-party platform or according to information input by the user.
The server establishes a corresponding health file for each user according to the acquired data such as blood sugar, blood pressure, diagnosis results, cases and the like.
And the user portrait analysis unit is used for analyzing the user portrait corresponding to the user identification according to the registration data, the behavior track and the health file.
And the user characteristic extraction unit is used for extracting the user characteristics corresponding to the user identification according to the user portrait.
Wherein, the user characteristic is a characteristic mark obtained by calculating the user portrait. The user portrait refers to a tagged user model abstracted according to social attributes, living habits and consumption behaviors, the core work of constructing the user portrait is to add tags to users, and the tags are feature identifications obtained through analyzing user information, namely user features.
Specifically, according to the application, the user characteristics corresponding to the user identification are obtained by calculating according to the registration data, the behavior data and the medical data of the user.
In one embodiment, the health data management apparatus further comprises:
the classification module is used for classifying a plurality of user identifications according to the user characteristics and adding class labels to the user identifications; the sending module is further configured to obtain a corresponding push message according to the category label, and send the push message corresponding to the category label to terminals corresponding to multiple user identifiers.
Specifically, a corresponding relationship among the user characteristics, the user identifiers and the user category labels is first established, and different user identifiers correspond to different user characteristics, or one user identifier corresponds to a plurality of user characteristics, that is, the category labels correspond to the user characteristics, and different user characteristics correspond to different category labels, and similarly, one user identifier may also correspond to a plurality of category labels.
The server can acquire the category label corresponding to the user identifier and send the push message corresponding to the category label to the terminals corresponding to the user identifiers according to the corresponding relationship between the category label and the push desired message.
In one embodiment, as shown in fig. 6, there is provided a health data management apparatus, further comprising: a data acquisition cycle presetting module 602, configured to preset a data acquisition cycle, and acquire behavior data and medical data in different data acquisition cycle segments.
The behavior data and the medical data of the user belong to dynamic data and are updated in real time, the registration data of the user belong to static data, and the recommended service items are adjusted according to user characteristics formed by the static data and the dynamic data in different period segments.
Specifically, the data acquisition period is a time interval at which the server acquires dynamic data of the user, that is, different time periods during which behavior data and medical data of the user are acquired, and the server periodically acquires the behavior data and the medical data of the user according to the set data acquisition period.
And a user characteristic obtaining module 604, configured to calculate user characteristics in different data obtaining periods according to the registration data, the behavior data in different data obtaining period segments, and the medical data.
Wherein, the user characteristic is a characteristic mark obtained by calculating the user portrait. The user portrait refers to a tagged user model abstracted according to social attributes, living habits and consumption behaviors, the core work of constructing the user portrait is to add tags to users, and the tags are feature identifications obtained through analyzing user information, namely user features.
Specifically, the registration data of the user belongs to static data, the behavior data and the medical data of the user belong to dynamic data, the behavior data and the medical data of the user can be updated in different period sections, and the server acquires the behavior data and the medical data in different period sections and calculates the user characteristics corresponding to the user identification in real time by combining the registration data.
And a recommended service item generation module 606, configured to match the user characteristic with the service keyword to obtain multiple recommended service items in different data acquisition periods.
In this embodiment, the server may calculate similarity values between the user features and the service keywords according to a similarity algorithm, determine a matching relationship between the user features and the service keywords according to the similarity values, and recommend the user according to the degree of the matching relationship.
Furthermore, an update cycle is preset for different service items, and in different update cycle segments, different service items, including recipes, drug dosage, fitness courses and the like, are adjusted correspondingly along with the updating of the behavior data and the medical data of the user so as to be matched with the updated user characteristics.
And the prompt information sending module 608 is configured to generate prompt information for health management by using a plurality of recommended service items, and send the prompt information to a terminal corresponding to a user identifier.
And producing prompt information of health management according to the service recommendation items, including the service items recommended to the user, prompt messages and the like.
Specifically, the service items recommended to the user include pushing health information and medical information, recommending health care products and slimming products, providing fitness courses and slimming courses, providing traditional Chinese medicine therapy and traditional Chinese medicine constitution conditioning, establishing health files of the user and the like, and the reminding message can be sent according to the fulfillment condition of the user and can also be generated according to the health courses selected by the user, the purchased health products and the like.
The health data management device sets a data acquisition period, acquires behavior data and medical data of a user in different period segments, generates user characteristics in different period segments in real time by combining with registration data, performs matching according to the user characteristics and service keywords, can acquire recommended service items in different period segments, provides real-time service for the user, simultaneously can send feedback information and a request for adjusting, replacing or optimizing the service items to a server, and can re-recommend the service items for the user after the server receives the feedback information or the request of the user, thereby realizing flexible personalized service management.
For the specific definition of the health data management device, reference may be made to the above definition of the health data management method, which is not described herein again. The various modules in the health data management device described above may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent of a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used to store health data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a health data management method.
Those skilled in the art will appreciate that the architecture shown in fig. 7 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, there is provided a computer device comprising a memory storing a computer program and a processor implementing the following steps when the processor executes the computer program:
acquiring registration data, behavior data and medical data corresponding to a plurality of user identifications;
calculating user characteristics corresponding to the user identification according to the registration data, the behavior data and the medical data;
acquiring a plurality of service items, and extracting corresponding service keywords according to the service items;
matching the user characteristics with the service keywords to obtain a plurality of recommended service items;
and generating prompt information of health management by using a plurality of recommended service items, and sending the prompt information to a terminal corresponding to the user identification.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring a plurality of preset motion fields and medical fields, and generating an SQL statement by using the motion fields and the medical fields;
respectively reading corresponding motion data and/or medical data in a plurality of source databases through the SQL sentences;
and writing the read motion data and/or medical data into a target database.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
classifying a plurality of user identifications according to the user characteristics, and adding category labels to the user identifications;
and acquiring corresponding push messages according to the category labels, and sending the push messages corresponding to the category labels to terminals corresponding to a plurality of user identifications.
In one embodiment, the processor when executing the computer program further performs the steps of:
presetting a question and an answer corresponding to the question, and storing the question and the answer in a database;
performing Chinese word segmentation on the question and an answer corresponding to the question;
classifying the answers after Chinese word segmentation based on a classification algorithm to obtain a plurality of answer categories;
acquiring a question input by a user;
executing matching operation according to the plurality of answer categories and the questions input by the user, and acquiring the question answer with the highest matching degree with the questions input by the user;
and pushing the question answer with the highest question matching degree input by the user to a terminal corresponding to the user identification.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring registration data, behavior data and medical data corresponding to a plurality of user identifications;
calculating user characteristics corresponding to the user identification according to the registration data, the behavior data and the medical data;
acquiring a plurality of service items, and extracting corresponding service keywords according to the service items;
matching the user characteristics with the service keywords to obtain a plurality of recommended service items;
and generating prompt information of health management by using a plurality of recommended service items, and sending the prompt information to a terminal corresponding to the user identifier.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a plurality of preset motion fields and medical fields, and generating an SQL statement by using the motion fields and the medical fields;
respectively reading corresponding motion data and/or medical data in a plurality of source databases through the SQL sentence;
and writing the read motion data and/or medical data into a target database.
In one embodiment, the computer program when executed by the processor further performs the steps of:
classifying a plurality of user identifications according to the user characteristics, and adding category labels to the user identifications;
and acquiring corresponding push messages according to the category labels, and sending the push messages corresponding to the category labels to terminals corresponding to a plurality of user identifications.
In one embodiment, the computer program when executed by the processor further performs the steps of:
presetting a question and an answer corresponding to the question, and storing the question and the answer in a database;
performing Chinese word segmentation on the question and an answer corresponding to the question;
classifying the answers subjected to Chinese word segmentation based on a classification algorithm to obtain a plurality of answer categories;
acquiring a question input by a user;
executing matching operation according to the plurality of answer categories and the questions input by the user, and acquiring the question answer with the highest matching degree with the questions input by the user;
and pushing the question answer with the highest question matching degree input by the user to a terminal corresponding to the user identification.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is specific and detailed, but not to be understood as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present patent application shall be subject to the appended claims.
Claims (9)
1. A method of health data management, the method comprising:
acquiring registration data, behavior data and medical data corresponding to a plurality of user identifications;
calculating user characteristics corresponding to the user identification according to the registration data, the behavior data and the medical data;
acquiring a plurality of service items, and extracting corresponding service keywords according to the service items;
matching the user characteristics with the service keywords to obtain a plurality of recommended service items;
generating prompt information of health management by using a plurality of recommended service items, and sending the prompt information to a terminal corresponding to a user identifier;
the calculating the user characteristics corresponding to the user identifier according to the registration data, the behavior data and the medical data comprises:
calculating a behavior track corresponding to the user identification according to the behavior data;
generating a health record corresponding to the user identification according to the medical data;
analyzing a user portrait corresponding to the user identification according to the registration data, the behavior track and the health file;
and extracting the user characteristics corresponding to the user identification according to the user portrait.
2. The method of claim 1, wherein the behavioral data comprises a motion field and the medical data comprises a medical field; the method further comprises the following steps:
acquiring a plurality of preset motion fields and medical fields, and generating an SQL statement by using the motion fields and the medical fields;
respectively reading corresponding motion data and/or medical data in a plurality of source databases through the SQL sentences;
and writing the read motion data and/or medical data into a target database.
3. The method according to any one of claims 1 to 2, further comprising:
classifying a plurality of user identifications according to the user characteristics, and adding category labels to the user identifications;
and acquiring corresponding push messages according to the category labels, and sending the push messages corresponding to the category labels to terminals corresponding to a plurality of user identifications.
4. The method according to any one of claims 1 to 2, further comprising:
presetting a data acquisition cycle, and acquiring behavior data and medical data in different data acquisition cycle segments;
calculating user characteristics in different data acquisition periods according to the registration data, the behavior data in different data acquisition period segments and the medical data;
matching the user characteristics with the service keywords to obtain a plurality of recommended service items in different data acquisition periods;
and generating prompt information of health management by using the plurality of recommended service items, and sending the prompt information to a terminal corresponding to the user identification.
5. A health data management apparatus, characterized in that the apparatus comprises:
the data acquisition module is used for acquiring registration data, behavior data and medical data corresponding to the user identifications;
the characteristic calculation module is used for calculating user characteristics corresponding to the user identification according to the registration data, the behavior data and the medical data;
the matching module is used for acquiring a plurality of service items and extracting corresponding service keywords according to the service items; matching the user characteristics with the service keywords to obtain a plurality of recommended service items;
the sending module is used for generating prompt information of health management by using a plurality of recommended service items and sending the prompt information to a terminal corresponding to the user identification;
the characteristic calculation module is further used for calculating a behavior track corresponding to the user identifier according to the behavior data; generating a health record corresponding to the user identification according to the medical data; analyzing a user portrait corresponding to the user identification according to the registration data, the behavior track and the health file; and extracting the user characteristics corresponding to the user identification according to the user portrait.
6. The apparatus of claim 5, further comprising:
the system comprises a synchronization module, a query module and a query module, wherein the synchronization module is used for acquiring a plurality of preset motion fields and medical fields and generating an SQL statement by using the motion fields and the medical fields; respectively reading corresponding motion data and/or medical data in a plurality of source databases through the SQL sentences; and writing the read motion data and/or medical data into a target database.
7. The apparatus of claim 5, further comprising:
the classification module is used for classifying a plurality of user identifications according to the user characteristics and adding class labels to the user identifications;
the sending module is further configured to obtain a corresponding push message according to the category label, and send the push message corresponding to the category label to terminals corresponding to multiple user identifiers.
8. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor when executing the computer program performs the steps of the method according to any of claims 1 to 4.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 4.
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Families Citing this family (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109948638B (en) * | 2018-12-04 | 2023-11-28 | 创新先进技术有限公司 | Object matching method, device, equipment and computer readable storage medium |
| CN109743363A (en) * | 2018-12-18 | 2019-05-10 | 广州圆爱康生物科技有限公司 | A kind of medical information intelligently pushing method and device |
| CN109671502A (en) * | 2018-12-18 | 2019-04-23 | 北京妙医佳信息技术有限公司 | Object portrait update method and device |
| CN109671503A (en) * | 2018-12-18 | 2019-04-23 | 北京妙医佳信息技术有限公司 | Healthy scheme evaluation method and device |
| CN111383737A (en) * | 2018-12-28 | 2020-07-07 | 康多富国际有限公司 | Cancer health food combination determination method and non-transitory computer-readable storage medium |
| CN109935340A (en) * | 2019-02-13 | 2019-06-25 | 国家体育总局体育科学研究所 | Management method, device and the electronic equipment of health data based on block chain |
| CN109933729A (en) * | 2019-03-28 | 2019-06-25 | 广州麦迪森在线医疗科技有限公司 | A kind of academic information recommended method of medical treatment based on user preference and system |
| CN110674392A (en) * | 2019-08-15 | 2020-01-10 | 阿里巴巴集团控股有限公司 | Project recommendation method and device based on historical health record |
| CN110706767A (en) * | 2019-08-30 | 2020-01-17 | 深圳壹账通智能科技有限公司 | Data processing method, device, equipment and storage medium |
| CN112992302A (en) * | 2019-12-12 | 2021-06-18 | 阿里巴巴集团控股有限公司 | Data processing method, device, equipment and storage medium |
| CN113539425A (en) * | 2020-04-20 | 2021-10-22 | 深圳市前海高新国际医疗管理有限公司 | Artificial intelligence data pushing system and method for body management |
| CN111739649B (en) * | 2020-07-04 | 2021-12-10 | 爱优牙信息技术(深圳)有限公司 | User portrait capturing method, device and system |
| CN112133431A (en) * | 2020-08-27 | 2020-12-25 | 绿瘦健康产业集团有限公司 | Health information message pushing method, device, medium and terminal equipment |
| CN112488893B (en) * | 2020-11-30 | 2023-11-17 | 泰康保险集团股份有限公司 | Service data processing method and device, storage medium and electronic equipment |
| CN112819548A (en) * | 2021-02-26 | 2021-05-18 | 泰康保险集团股份有限公司 | User portrait generation method and device, readable storage medium and electronic equipment |
| CN113724823B (en) * | 2021-08-31 | 2024-04-05 | 深圳平安智慧医健科技有限公司 | On-line management method, device, equipment and storage medium for medical health service |
| CN115579104B (en) * | 2022-09-08 | 2024-07-12 | 广东技术师范大学 | Manual intelligent-based liver cancer whole course digital management method and system |
| CN115394394B (en) * | 2022-10-27 | 2023-04-07 | 曹县人民医院 | Resident health service reservation method and system based on big data processing technology |
| CN117454017B (en) * | 2023-12-21 | 2024-04-02 | 广州平云小匠科技股份有限公司 | Course recommendation method, device and storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106815786A (en) * | 2017-03-27 | 2017-06-09 | 广东德生科技股份有限公司 | A kind of medical services signing system and method |
| CN107291739A (en) * | 2016-03-31 | 2017-10-24 | 阿里巴巴集团控股有限公司 | Evaluation method, system and the equipment of network user's health status |
| CN107566538A (en) * | 2017-10-30 | 2018-01-09 | 江西博瑞彤芸科技有限公司 | Information-pushing method and system |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017022015A1 (en) * | 2015-07-31 | 2017-02-09 | 株式会社ＦｉＮＣ | Health management server, health-management-server control method, and health management program |
-
2018
- 2018-05-31 CN CN201810547720.8A patent/CN108766512B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107291739A (en) * | 2016-03-31 | 2017-10-24 | 阿里巴巴集团控股有限公司 | Evaluation method, system and the equipment of network user's health status |
| CN106815786A (en) * | 2017-03-27 | 2017-06-09 | 广东德生科技股份有限公司 | A kind of medical services signing system and method |
| CN107566538A (en) * | 2017-10-30 | 2018-01-09 | 江西博瑞彤芸科技有限公司 | Information-pushing method and system |
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