CN117238506A

CN117238506A - Health assessment method, apparatus, computer device and storage medium

Info

Publication number: CN117238506A
Application number: CN202311452862.3A
Authority: CN
Inventors: 熊慧萍
Original assignee: Ping An Health Insurance Company of China Ltd
Current assignee: Ping An Health Insurance Company of China Ltd
Priority date: 2023-11-02
Filing date: 2023-11-02
Publication date: 2023-12-15

Abstract

The embodiment of the application belongs to the field of artificial intelligence and digital medical treatment, and is applied to the field of digital medical treatment systems, and relates to a health assessment method, which comprises the steps of acquiring questionnaire data of a user to be assessed, wherein the questionnaire data is generated after completion of assessment questionnaire filling for the user to be assessed, and the questions of the assessment questionnaire are dynamically adjusted according to the above semantics filled by the user to be assessed; determining an evaluation model of the user to be evaluated according to the questionnaire data; and determining a health evaluation result of the user to be evaluated based on the questionnaire data and the evaluation model. The application also provides a health assessment device, computer equipment and a storage medium. According to the application, the questionnaire data is generated after the user to be evaluated fills out the evaluation questionnaire, and the evaluation questionnaire is dynamically adjusted according to the semantic meaning filled out by the user, so that the obtained questionnaire data is related to the semantic meaning of the user to be evaluated, and the questionnaire data which is more concerned by the user to be evaluated can be further mined, thereby improving the accuracy of health evaluation.

Description

Health assessment method, apparatus, computer device and storage medium

Technical Field

The present application relates to the field of artificial intelligence and digital medical technology, and more particularly, to a health assessment method, apparatus, computer device, and storage medium.

Background

Traditional medical institutions collect questionnaires for patients based on related international/domestic normative standards, mostly in the form of scoring scales. Based on the scale and the health data, analysis and evaluation are manually carried out, medical resources are occupied, and the overall efficiency is low. The existing large health management platforms gradually optimize and push out health assessment based on models. The existing health management platform mainly aims at different disease types and designs corresponding questionnaire contents to carry out health assessment, and because the questionnaire contents are fixedly designed for single disease types, health data obtained according to questionnaires are relatively fixed, and because of the difference of personal bodies of users, the health data are different, if the health assessment is carried out only by the questionnaires with the fixedly designed, the problem of low accuracy of health assessment results can be caused.

Disclosure of Invention

The embodiment of the application aims to provide a health evaluation method, a health evaluation device, computer equipment and a storage medium, which are used for solving the problem that the accuracy of a health evaluation result is not high when only a questionnaire with a fixed design is used for health evaluation in a health evaluation system.

In order to solve the above technical problems, the embodiment of the present application provides a health assessment method, which adopts the following technical scheme:

Acquiring questionnaire data of a user to be evaluated, wherein the questionnaire data is generated after the user to be evaluated fills out an evaluation questionnaire, and the questions of the evaluation questionnaire are dynamically adjusted according to the above semantics filled out by the user to be evaluated;

determining an evaluation model of the user to be evaluated according to the questionnaire data;

and determining a health evaluation result of the user to be evaluated based on the questionnaire data and the evaluation model.

Further, before the step of acquiring the questionnaire data of the user, the method further includes:

determining a user to be evaluated, and determining an evaluation item of the user to be evaluated;

determining an evaluation questionnaire of the user to be evaluated based on the evaluation items of the user to be evaluated;

and sending the evaluation questionnaire to the user to be evaluated so as to acquire questionnaire data of the user to be evaluated.

Further, the step of determining the evaluation item of the user to be evaluated specifically includes:

acquiring crowd characteristics of the user to be evaluated;

and determining the evaluation items of the users to be evaluated based on the crowd characteristics of the users to be evaluated.

Further, the step of sending the evaluation questionnaire to the user to be evaluated to obtain questionnaire data of the user to be evaluated specifically includes:

When the user to be evaluated is detected to finish any question in the evaluation questionnaire, acquiring the finished question and an answer of the finished question;

determining a next question based on the completed question and an answer to the completed question;

and acquiring questionnaire data of the user to be evaluated when detecting that the user to be evaluated completes all the questions in the questionnaire to be evaluated.

Further, the step of determining a next question of the evaluation questionnaire based on the completed question and an answer to the completed question specifically includes:

determining semantic features of the user to be evaluated based on the completed questions and answers to the completed questions;

determining the current intention of the user to be evaluated based on the semantic features of the user to be evaluated;

based on the current intention of the user to be evaluated, determining the next question of the evaluation questionnaire.

Further, the step of determining the evaluation model of the user to be evaluated according to the questionnaire data specifically includes:

determining a target disease type of the user to be evaluated according to the questionnaire data;

and determining an evaluation model of the user to be evaluated based on the target disease, wherein the evaluation model corresponds to the target disease.

Further, after the step of determining the health evaluation result of the user to be evaluated based on the questionnaire data and the evaluation model, the method further includes:

determining a feedback result of the user to be evaluated based on the health evaluation result;

and establishing a health file of the user to be evaluated based on the feedback result of the user to be evaluated.

In order to solve the above technical problems, the embodiment of the present application further provides a health assessment device, which adopts the following technical scheme:

the acquisition module is used for acquiring questionnaire data of the user to be evaluated, wherein the questionnaire data is generated after the user to be evaluated fills out an evaluation questionnaire, and the evaluation questionnaire is dynamically adjusted according to the above semantics filled out by the user to be evaluated;

the model determining module is used for determining an evaluation model of the user to be evaluated according to the questionnaire data;

and the evaluation module is used for determining the health evaluation result of the user to be evaluated based on the questionnaire data and the evaluation model.

In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical schemes:

The computer device includes a memory having stored therein computer readable instructions that when executed by the processor implement the steps of the health assessment method of any of the embodiments of the present application.

In order to solve the above technical problems, an embodiment of the present application further provides a computer readable storage medium, which adopts the following technical schemes:

the computer readable storage medium has stored thereon computer readable instructions which when executed by a processor implement the steps of the health assessment method according to any of the embodiments of the present application

Compared with the prior art, the embodiment of the application has the following main beneficial effects: after acquiring the questionnaire data of the user to be evaluated, determining a corresponding evaluation model according to the questionnaire data, and processing the questionnaire data by utilizing the evaluation model to obtain a health evaluation result of the user to be evaluated.

Drawings

In order to more clearly illustrate the solution of the present application, a brief description will be given below of the drawings required for the description of the embodiments of the present application, it being apparent that the drawings in the following description are some embodiments of the present application, and that other drawings may be obtained from these drawings without the exercise of inventive effort for a person of ordinary skill in the art.

FIG. 1 is an exemplary system architecture diagram in which the present application may be applied;

FIG. 2 is a flow chart of one embodiment of a health assessment method according to the present application;

FIG. 3 is a flow chart of an embodiment prior to step S201 in FIG. 2;

FIG. 4 is a flow chart of one embodiment of step S301 in FIG. 3;

FIG. 5 is a flow chart of one embodiment of step S303 of FIG. 4;

FIG. 6 is a flow chart of one embodiment of step S3032 in FIG. 5;

FIG. 7 is a flow chart of one embodiment of step S202 of FIG. 2;

FIG. 8 is a flow chart of one embodiment of step S203 of FIG. 2;

FIG. 9 is a schematic diagram of a configuration of one embodiment of a health assessment device according to the present application;

FIG. 10 is a schematic diagram illustrating a structure of an embodiment of the health assessment device 900 of FIG. 9;

FIG. 11 is a schematic diagram of an embodiment of the item determination module 904 of FIG. 9;

FIG. 12 is a schematic diagram illustrating the structure of one embodiment of the transmit module 906 of FIG. 11;

FIG. 13 is a schematic diagram illustrating a configuration of one embodiment of the second determination submodule 9062 of FIG. 12;

FIG. 14 is a schematic diagram of one embodiment of the model determination module 902 of FIG. 9;

FIG. 15 is a schematic diagram illustrating a structure of an embodiment of the health assessment device 900 of FIG. 9;

FIG. 16 is a schematic structural view of one embodiment of a computer device according to the present application.

Detailed Description

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used in the description of the applications herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having" and any variations thereof in the description of the application and the claims and the description of the drawings above are intended to cover a non-exclusive inclusion. The terms first, second and the like in the description and in the claims or in the above-described figures, are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

In order to make the person skilled in the art better understand the solution of the present application, the technical solution of the embodiment of the present application will be clearly and completely described below with reference to the accompanying drawings.

As shown in fig. 1, a system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.

The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like. Various communication client applications, such as a web browser application, a shopping class application, a search class application, an instant messaging tool, a mailbox client, social platform software, etc., may be installed on the terminal devices 101, 102, 103.

The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablet computers, electronic book readers, MP3 players (Moving Picture ExpertsGroup Audio Layer III, dynamic video expert compression standard audio plane 3), MP4 (Moving PictureExperts Group Audio Layer IV, dynamic video expert compression standard audio plane 4) players, laptop and desktop computers, and the like.

The server 105 may be a server providing various services, such as a background server providing support for pages displayed on the terminal devices 101, 102, 103.

It should be noted that, the health assessment method provided by the embodiment of the present application is generally executed by a server/terminal device, and accordingly, the health assessment apparatus is generally disposed in the server/terminal device.

It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

With continued reference to FIG. 2, a flow chart of one embodiment of a health assessment method according to the present application is shown. The health evaluation method comprises the following steps:

Step S201, acquiring questionnaire data of a user to be evaluated.

In this embodiment, the electronic device (for example, the server shown in fig. 1) on which the health evaluation method operates may receive the query request of the terminal device through a wired connection manner or a wireless connection manner. It should be noted that the wireless connection may include, but is not limited to, 3G/4G/5G connection, wiFi connection, bluetooth connection, wiMAX connection, zigbee connection, UWB (ultra wideband) connection, and other now known or later developed wireless connection.

The terminal equipment can be terminal equipment with remote interaction functions, such as personal assistants, intelligent customer service and the like, and the health assessment method can be applied to services such as online health management, online health consultation and online data query.

Specifically, the electronic device can be used for question configuration, questionnaire configuration and health assessment configuration.

The question configuration may include different question content configurations, and may specifically include configurations of question contents such as a single selection/multiple selection/question and answer/material upload/combination component. The topic content can be determined by the communication between the operator and the doctor/health care professional, or can be automatically generated based on a language generation model.

The questionnaire configuration may include a configuration of setting a question type, a question content, a question trigger condition, and the like in the evaluation questionnaire, and the evaluation questionnaire may perform front-back end streaming control in a tree structure or perform front-back end streaming control in a language generation model.

The health evaluation configuration may configure a corresponding model based on the evaluation items of the questionnaire library, and the health evaluation configuration may specifically include the configuration of disease types, crowd characteristics, model rules, and the like. The evaluation model may include an evaluation model of different disease species, which is used for health evaluation and feedback of different disease species.

Specifically, in the questionnaire configuration, each question in the evaluation questionnaire can be used as a node, front-end and back-end flow control is performed through a tree structure, when the evaluation questionnaire is filled in by a user to be evaluated, each time a question is completed at the front end, the back end can inquire a child node under the node corresponding to the question, and the searched question corresponding to the child node is sent to the front end, so that front-end and back-end flow control among the questions in the evaluation questionnaire is realized. The above semantics of each question in the front-end evaluation questionnaire can be input into a language generation model of the back-end, the corresponding questions of the above semantics are generated and transmitted back to the front-end, and therefore front-end and back-end flow control among the questions in the evaluation questionnaire is achieved. The front end corresponds to a terminal device, and the back end corresponds to a server.

The user to be evaluated can input answers of all the questions in the evaluation questionnaire through the terminal equipment, and after the evaluation questionnaire is completed, the server receives the questions of the evaluation questionnaire and answers corresponding to the questions, and questionnaire data of the user to be evaluated are obtained. The questions and answers corresponding to the questions may be text data or non-text data, and if the questions or answers corresponding to the questions are non-text data, the non-text data may be converted into text data for processing. The above non-text data may be voice data, image data, or the like.

Step S202, determining an evaluation model of the user to be evaluated according to the questionnaire data.

In this embodiment, the disease type of interest of the user to be evaluated may be determined through questionnaire data, and the evaluation model of the user to be evaluated may be truly derived according to the disease type of interest of the user to be evaluated. The evaluation model may include an evaluation model of different disease species, which is used for health evaluation and feedback of different disease species. Namely, after the interesting disease types of the user to be evaluated are determined, the evaluation model corresponding to the interesting disease types of the user to be evaluated can be truly obtained according to the mapping relation between the disease types and the evaluation model, and the evaluation model corresponding to the interesting disease types of the user to be evaluated is determined as the evaluation model of the user to be evaluated.

The evaluation model may be a trained evaluation model, and further, the evaluation model is an AI evaluation model, and the AI evaluation model is obtained by training health data as a training corpus.

The AI evaluation model can be constructed based on convolutional neural network CNN, cyclic neural network RNN, long-short-term memory network LSMT, etc. The health data can be obtained by grabbing in an open source data network by a compliant technical means, or can be obtained by self-collection of developers.

Step S203, based on the questionnaire data and the evaluation model, determining the health evaluation result of the user to be evaluated.

In this embodiment, after obtaining the questionnaire data and determining the evaluation model, the electronic device may input the questionnaire data into the evaluation model to process the questionnaire data, to obtain a processing result of the evaluation model, and may determine the processing result of the evaluation model as a health evaluation result of the user to be evaluated. The analysis can also be performed on the basis of the processing result to obtain a health evaluation result of the user to be evaluated, the health evaluation result of the user to be evaluated is returned to the terminal equipment of the user to be evaluated, and the health evaluation result of the user to be evaluated is returned to the terminal equipment of the doctor/health care manager.

The processing result can comprise crowd grouping, crowd labels, medical indexes and other data, and the data of the crowd grouping, the crowd labels, the medical indexes and the like can be intelligently analyzed through an AI intelligent analysis tool to obtain health assessment results of users to be assessed.

Further, when the health evaluation result of the user to be evaluated is obtained, the health evaluation result of the user to be evaluated can be stored in a corresponding database for reference.

After acquiring the questionnaire data of the user to be evaluated, the application determines the corresponding evaluation model according to the questionnaire data, processes the questionnaire data by utilizing the evaluation model, and can obtain the health evaluation result of the user to be evaluated.

With continued reference to fig. 3, a flow chart of one embodiment is shown prior to step S201 in fig. 2. Before step S201, the health assessment method further includes the steps of:

S301, determining a user to be evaluated, and determining evaluation items of the user to be evaluated.

In this embodiment, the user to be evaluated is a user initiating a health evaluation, such as a user of an end device who wants to perform an online health evaluation and an online health consultation.

In a possible embodiment, the evaluation items of the user to be evaluated may be determined by the user to be evaluated by selecting the user to be evaluated by himself, specifically, the terminal device may display the evaluation items in a classified manner through an interactive interface, the user may select the evaluation item of interest through the interactive interface, and the electronic device may determine the evaluation item of the user to be evaluated according to the evaluation item selected by the user to be evaluated at the interactive interface of the terminal device.

In a possible embodiment, the evaluation items of the user to be evaluated may be determined according to the recommendation of the doctor/health care provider, the electronic device receives the recommendation of the evaluation items from the terminal device of the doctor/health care provider, and recommends the evaluation items to the user to be evaluated according to the recommendation of the evaluation items, and when the user to be evaluated accepts the recommendation, the recommended evaluation items are determined as the evaluation items of the user to be evaluated.

In a possible embodiment, the evaluation items of the user to be evaluated may be determined according to assistance of a doctor/health care provider, the doctor/health care provider may assist the user to be evaluated in determining the evaluation items in an offline manner, and the electronic device receives the evaluation items from the terminal device of the user/doctor/health care provider to be evaluated and determines the evaluation items as the evaluation items of the user to be evaluated.

The evaluation items may include evaluation items corresponding to different disease types, such as hypertension, hyperglycemia, hyperlipidemia, pulmonary nodules, obesity, etc., different populations, such as normal population, early population, middle population, late population, etc., and different model tasks, such as questionnaire tasks, evaluation tasks, etc.

S302, determining an evaluation questionnaire of the user to be evaluated based on the evaluation items of the user to be evaluated.

In this embodiment, different evaluation items correspond to different evaluation questionnaires, if the evaluation item of the user to be evaluated is a disease type, such as hypertension, the type of the evaluation questionnaire is also an evaluation questionnaire corresponding to hypertension, if the evaluation item of the user to be evaluated is an early crowd, the type of the evaluation questionnaire is also an evaluation questionnaire corresponding to early crowd, and if the evaluation item of the user to be evaluated is a health evaluation, the type of the evaluation questionnaire is also an evaluation questionnaire corresponding to health evaluation.

For the corresponding relation between the evaluation items and the evaluation questionnaires, maintenance can be performed through a mapping table, wherein different evaluation items correspond to different evaluation questionnaires in the mapping table. After the evaluation items are determined, the corresponding evaluation questionnaires can be found through the corresponding relations in the mapping table.

S303, sending the evaluation questionnaire to the user to be evaluated so as to acquire questionnaire data of the user to be evaluated.

In this embodiment, after determining the evaluation questionnaire of the user to be evaluated, the electronic device may improve the evaluation questionnaire to the terminal device of the user to be evaluated, so that the user to be evaluated answers the received evaluation questionnaire, after completing the answers of all the questions in the evaluation questionnaire, the terminal device uploads the answers of all the questions and the questions in the evaluation questionnaire as questionnaire data to the electronic device, and after receiving the questionnaire data, the electronic device obtains the questionnaire data of the user to be evaluated. It should be noted that the questionnaire data includes questions and answers of the questions, and each question corresponds to one answer.

According to the method and the device for evaluating the questionnaire, the user to be evaluated and the evaluation items thereof are determined, so that the evaluation questionnaire which is suitable for the user to be evaluated can be matched, the questionnaire data of the user to be evaluated is more accurate, and the health evaluation accuracy of the user to be evaluated is further improved.

With continued reference to FIG. 4, a flowchart of one embodiment of step S301 of FIG. 3 is shown. In step S301, the method specifically includes the following steps:

step S3011, obtaining crowd characteristics of the user to be evaluated.

In this embodiment, the crowd characteristics of the user to be evaluated may be determined according to medical record data, or may be determined by historical health evaluation data, and when the user to be evaluated is a new user and there is no historical health evaluation data, the crowd characteristics of the user to be evaluated may be determined by calling the medical record data in the medical system.

The crowd characteristics are used for describing which crowd the user to be evaluated belongs to, and different crowd characteristics correspond to different crowd characteristics, such as early crowd, middle crowd and late crowd of cancer respectively correspond to different crowd characteristics.

The electronic device can acquire medical record data and historical health evaluation data of the user to be evaluated to determine crowd characteristics of the user to be evaluated.

Step S3012, determining an evaluation item of the user to be evaluated based on the crowd characteristics of the user to be evaluated.

In this embodiment, different crowd characteristics correspond to different evaluation items, and the evaluation items of the user to be evaluated may be determined according to the crowd characteristics of the user to be evaluated.

Specifically, the electronic device may obtain crowd characteristics of the user to be evaluated, classify the crowd characteristics according to the crowd characteristics, and recommend evaluation items to the user to be evaluated according to classification results, and after the user to be evaluated accepts the recommendation, determine the recommended evaluation items as evaluation items of the user to be evaluated.

And maintaining a relation mapping table between the crowd characteristics and the evaluation items in the electronic equipment, and searching the corresponding evaluation items according to the relation mapping table after determining the crowd characteristics of the user to be evaluated.

According to the method and the device for evaluating the questionnaire, the evaluation items of the user to be evaluated are determined through the crowd characteristics, so that the evaluation items of the user to be evaluated are adapted to the corresponding crowd, the selection range of the evaluation questionnaire is further reduced, and the accuracy of the evaluation questionnaire is improved.

With continued reference to fig. 5, a flowchart of one embodiment of step S303 of fig. 4 is shown. In step S303, the method specifically includes the following steps:

step S3031, when the user to be evaluated finishes evaluating any question in the questionnaire, the completed question and the answer of the completed question are obtained.

In this embodiment, the evaluation questionnaire may include dynamic questions, and each time the user to be evaluated answers one question, the next question is dynamically adjusted according to the question that the user to be evaluated previously answered.

After the electronic device sends the evaluation questionnaire to the terminal device, a user can fill in the evaluation questionnaire through an interaction interface of the terminal device, the electronic device can detect the filling progress of the evaluation questionnaire, and when detecting that the user to be evaluated finishes any question in the evaluation questionnaire, the electronic device can acquire the finished question and an answer of the finished question.

In one possible embodiment, the evaluation questionnaire may include a fixed question and a dynamic question, where the fixed question refers to a question that does not change with an answer of the user to be evaluated, and the dynamic question refers to a question that may change with an answer of the user to be evaluated.

Specifically, the first n questions in the evaluation questionnaire can be fixed questions, n is greater than or equal to 1, and the fixed questions can be used as starting dependence of the dynamic questions, mainly providing the above data for the dynamic questions, and avoiding overlarge deviation of the questions of the evaluation questionnaire caused by cold starting of the dynamic questions.

Step S3032, the next question is determined based on the completed question and the answer to the completed question.

In this embodiment, after the electronic device obtains the completed title and the answer of the completed title, the electronic device may perform front-back end streaming control by using the tree structure or perform front-back end streaming control by using the language generation model, so as to obtain a new title and send the new title to the terminal device.

Specifically, the keyword can be extracted through the completed questions and answers of the completed questions, the sub-nodes corresponding to the keyword are searched out from the nodes of the tree structure through the keyword, the questions in the sub-nodes are determined to be the next questions, the next questions are sent to the terminal equipment for the users to be evaluated to answer, and the evaluation questionnaires are synchronously updated on the terminal equipment and the electronic equipment.

The completed questions and answers of the completed questions can be input into a language generation model in the electronic equipment for generation processing, so that the completed questions and the next questions corresponding to the answers of the completed questions are obtained, and the next questions are sent to the terminal equipment for the users to be evaluated to answer, and the evaluation questionnaires are synchronously updated on the terminal equipment and the electronic equipment.

Step S3033, when the user to be evaluated is detected to finish evaluating all the questions in the questionnaire, questionnaire data of the user to be evaluated is obtained.

In this embodiment, after the electronic device sends the evaluation questionnaire to the terminal device, the user may fill in the evaluation questionnaire through the interaction interface of the terminal device, the electronic device may detect the filling progress of the evaluation questionnaire, and when detecting that the user to be evaluated completes all the questions in the evaluation questionnaire, may obtain the completed questions and the answers of the completed questions, and use the completed questions and the answers of the completed questions as the questionnaire data of the user to be evaluated.

The questions for evaluating the questionnaire comprise dynamic questions, the next question can be adaptively output according to the answer content of the completed questions, and further, under the condition that the intention of a user is understood, questionnaire data which are interested by the user to be evaluated can be acquired through the dynamic questions, so that the accuracy of health evaluation is further improved.

With continued reference to fig. 6, a flow chart of one embodiment of step S3032 in fig. 5 is shown. In step S3032, the method specifically includes the following steps:

step S30321, determining semantic features of the user to be evaluated based on the completed questions and the answers to the completed questions.

In this embodiment, when the electronic device obtains the completed question and the answer of the completed question, the completed question and the answer of the completed question may be processed into one piece of text data to be processed, the text data to be processed is input into the semantic extraction model, the semantic features of the text data to be processed are extracted, and the semantic features of the text data to be processed may be determined as the semantic features of the user to be evaluated.

The semantic extraction model may be a natural language processing model (Natural LanguageHale Waihona Puke BaiduProcessing, NLP), such as Word2vec, fastext, glove, elmo, bert, etc.

Step S30322, determining the current intention of the user to be evaluated based on the semantic features of the user to be evaluated.

In this embodiment, all intentions may be converted into feature vectors, after the semantic features of the user to be evaluated are obtained, the distance between the semantic features and the feature vectors may be calculated, and the intent corresponding to the feature vector with the smallest distance may be determined as the current intent of the user to be evaluated.

The current intent is used to represent content of interest to the user to be evaluated.

Step S30323, the next question of the evaluation questionnaire is determined based on the current intention of the user to be evaluated.

In this embodiment, after obtaining the current intention of the user to be evaluated, searching for a child node corresponding to the current intention in the nodes of the tree structure through the current intention, determining the question in the child node as the next question, sending the next question to the terminal device for the user to be evaluated to answer, and synchronously updating the evaluation questionnaire on the terminal device and the electronic device.

The method can also input the current intention into a language generation model in the electronic equipment for generation processing, obtain the next question corresponding to the current intention, send the next question to the terminal equipment for the user to be evaluated to answer, and synchronously update the evaluation questionnaire on the terminal equipment and the electronic equipment.

The application utilizes the completed questions and answers of the completed questions to determine the semantic features of the user to be evaluated, determines the current intention of the user to be evaluated according to the semantic features of the user to be evaluated, improves the accuracy of the current intention, and obtains the next questions of the evaluation questionnaire according to the current intention, so that the evaluation questionnaire can describe the questionnaire data of the user to be evaluated more accurately, and improves the accuracy of health evaluation.

With continued reference to FIG. 7, a flow chart of one embodiment of step S202 of FIG. 2 is shown. In step S202, the method specifically includes the following steps:

in step S2021, the target disease type of the user to be evaluated is determined according to the questionnaire data.

In this embodiment, when the electronic device obtains the questionnaire data, the target disease type of the user to be evaluated may be determined according to the keywords or semantics of the questionnaire data.

Further, each disease seed has a corresponding keyword, after the keywords are extracted from the questionnaire data, the corresponding relation between the keywords and the disease seed is utilized to find the disease seed corresponding to the keywords as the target disease seed of the user to be evaluated.

Each disease has corresponding semantics, after extracting the semantics from the questionnaire data, the corresponding relation between the semantics and the disease is utilized to find the disease corresponding to the semantics as the target disease of the user to be evaluated.

Step S2022, determining an evaluation model of the user to be evaluated based on the target disease.

In this embodiment, the evaluation model has a correspondence with the target disease, after determining the evaluation model of the user to be evaluated, the corresponding evaluation model may be found according to the correspondence between the target disease and the evaluation model, and the evaluation model may be determined as the evaluation model of the user to be evaluated.

According to the method and the device for evaluating the health of the user, the target disease types of interest of the user to be evaluated are determined through the questionnaire data, and then the questionnaire data is processed by finding the most suitable evaluation model according to the target disease types, so that the processing result is more accurate, and the accuracy of health evaluation is improved.

With continued reference to fig. 8, a flow chart of one embodiment of step S203 of fig. 2 is shown. In step S203, the method specifically includes the following steps:

step S2031, determining a feedback result of the user to be evaluated based on the health evaluation result.

In this embodiment, the health evaluation result may be directly returned to the user to be evaluated and the doctor/health care provider as a feedback result of the user to be evaluated.

The feedback result can be the result feedback of evaluation crowd grouping, grouping crowd evaluation feedback, crowd labels and medical index trend analysis, and the feedback result information client and doctor/health care manager can check and reference the results, so that the data is provided for continuous health plans and follow-up plans of subsequent clients.

Step S2032, establishing a health profile of the user to be evaluated based on the feedback result of the user to be evaluated.

In this embodiment, a health record may be established for the user to be evaluated, and the health evaluation result and the feedback result may be stored in the health record. The method specifically can collect the content of the evaluation questionnaire and the conclusion and the client label of model evaluation feedback, write back and store the content and the client label to the client health file, and support the client health condition viewing of other subsequent scenes.

The application can provide a health reference basis for health management of patients by returning feedback results to the users to be evaluated and doctors/health care givers and documenting and storing related data of health evaluation, can carry out crowd grouping suggestion based on the evaluation, and is an important link in building the full life cycle health management of clients.

Specifically, the application can support the health assessment of the disease-classifying and characteristic-classifying crowd based on the health assessment construction of the model, and can pertinently carry out model assessment feedback of the corresponding disease types/crowd after the assessment content is collected, and recommend corresponding health suggestions and subsequent health management schemes based on the feedback. The evaluation data and the model feedback and AI intelligent analysis provide a health reference basis for the health management of patients of medical care crowds, and crowd grouping suggestion can be carried out based on the evaluation. The health evaluation construction supports the whole flow function of the evaluation feedback design based on crowd grouping/medical indexes from the topic design, the questionnaire design and the topic jump rule design, the health evaluation design and the evaluation model design, and is an important link in the construction of the whole life cycle health management of clients.

The embodiment of the application can acquire and process the related data required by the knowledge base configuration based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.

Artificial intelligence infrastructure technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and other directions. The application can be applied to on-line health management and on-line health consultation, thereby promoting the construction of digital medical treatment.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by computer readable instructions stored in a computer readable storage medium that, when executed, may comprise the steps of the embodiments of the methods described above. The storage medium may be a nonvolatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a random access Memory (Random Access Memory, RAM).

It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the flowcharts of the figures may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily being sequential, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.

With further reference to fig. 9, as an implementation of the method shown in fig. 2 described above, the present application provides an embodiment of a health assessment apparatus, which corresponds to the method embodiment shown in fig. 2, and which is particularly applicable to various electronic devices.

As shown in fig. 9, the health evaluation device 900 according to the present embodiment includes: an acquisition module 901, a model determination module 902, an evaluation module 903. Wherein:

the acquiring module 901 is configured to acquire questionnaire data of a user to be evaluated, where the questionnaire data is generated after the user to be evaluated fills out an evaluation questionnaire, and the evaluation questionnaire is dynamically adjusted according to the above semantics filled out by the user to be evaluated;

the model determining module 902 is configured to determine an evaluation model of the user to be evaluated according to the questionnaire data;

and the evaluation module 903 is configured to determine a health evaluation result of the user to be evaluated based on the questionnaire data and the evaluation model.

Referring to fig. 10, which is a schematic structural diagram of an embodiment of the health assessment apparatus 900 in fig. 9, in some alternative implementations of the present embodiment, the obtaining module 901 includes an item determining module 904, a questionnaire determining module 905, and a processing sub-module 905. Wherein:

an item determining module 904, configured to determine a user to be evaluated, and determine an evaluation item of the user to be evaluated;

a questionnaire determining module 905, configured to determine an evaluation questionnaire of the user to be evaluated based on the evaluation items of the user to be evaluated;

and a sending module 906, configured to send the evaluation questionnaire to the user to be evaluated, so as to obtain questionnaire data of the user to be evaluated.

Referring to fig. 11, which is a schematic structural diagram of an embodiment of the item determining module 904 in fig. 9, the item determining module 904 includes a first obtaining sub-module 9041 and a first determining sub-module 9042. Wherein:

a first obtaining submodule 9041, configured to obtain crowd characteristics of the user to be evaluated;

A first determining submodule 9042, configured to determine an evaluation item of the user to be evaluated based on crowd characteristics of the user to be evaluated.

Referring to fig. 12, which is a schematic structural diagram of an embodiment of the sending module 906 in fig. 11, the sending module 906 includes a second obtaining sub-module 9061, a second determining sub-module 9062, and a third obtaining sub-module 9063. Wherein:

the second obtaining sub-module 9061 is configured to obtain a completed question and an answer to the completed question when detecting that the user to be evaluated completes any question in the evaluation questionnaire;

a second determining submodule 9062, configured to determine a next question based on the completed question and an answer to the completed question;

and a third obtaining sub-module 9063, configured to obtain questionnaire data of the user to be evaluated when detecting that the user to be evaluated completes all the questions in the questionnaire to be evaluated.

Referring to fig. 13, a schematic structural diagram of an embodiment of the second determining submodule 9062 in fig. 12, where the second determining submodule 9062 includes a first determining unit 90621, a second determining unit 90622, and a third determining unit 90623. Wherein:

a first determining unit 90621 that determines semantic features of the user to be evaluated based on the completed questions and answers to the completed questions;

a second determining unit 90622 that determines a current intention of the user to be evaluated based on semantic features of the user to be evaluated;

a third determining unit 90623 for determining a next question of the evaluation questionnaire based on the current intention of the user to be evaluated.

Referring to fig. 14, which is a schematic structural diagram of an embodiment of the model determining module 902 in fig. 9, the model determining module 902 includes a disease determining sub-module 9021 and a post-processing sub-module 9022. Wherein:

A disease type determining submodule 9021, configured to determine a target disease type of the user to be evaluated according to the questionnaire data;

and a model determining submodule 9022, configured to determine an evaluation model of the user to be evaluated based on the target disease, where the evaluation model corresponds to the target disease.

Referring to fig. 15, which is a schematic structural diagram of an embodiment of the health assessment apparatus 900 in fig. 9, the health assessment apparatus 900 includes a feedback result determining module 907 and a file creating module 908. Wherein:

a feedback result determining module 907, configured to determine a feedback result of the user to be evaluated based on the health evaluation result;

and a profile creation module 908, configured to create a health profile of the user to be evaluated based on the feedback result of the user to be evaluated.

In order to solve the technical problems, the embodiment of the application also provides computer equipment. Referring specifically to fig. 16, fig. 16 is a basic structural block diagram of a computer device according to the present embodiment.

The computer device 16 includes a memory 161, a processor 162, and a network interface 163 communicatively coupled to each other via a system bus. It should be noted that only computer device 16 having components 161-163 is shown in the figures, but it should be understood that not all of the illustrated components need be implemented, and that more or fewer components may be implemented instead. It will be appreciated by those skilled in the art that the computer device herein is a device capable of automatically performing numerical calculations and/or information processing in accordance with predetermined or stored instructions, the hardware of which includes, but is not limited to, microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASICs), programmable gate arrays (fields-Programmable Gate Array, FPGAs), digital processors (Digital Signal Processor, DSPs), embedded devices, etc.

The computer equipment can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing equipment. The computer equipment can perform man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch pad or voice control equipment and the like.

The memory 161 includes at least one type of readable storage medium including flash memory, hard disk, multimedia card, card memory (e.g., SD or DX memory, etc.), random Access Memory (RAM), static Random Access Memory (SRAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), programmable Read Only Memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 161 may be an internal storage unit of the computer device 16, such as a hard disk or a memory of the computer device 16. In other embodiments, the memory 161 may also be an external storage device of the computer device 16, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the computer device 16. Of course, the memory 161 may also include both internal storage units of the computer device 16 and external storage devices. In this embodiment, the memory 161 is typically used to store an operating system and various types of application software installed on the computer device 16, such as computer readable instructions for a health assessment method. Further, the memory 161 may be used to temporarily store various types of data that have been output or are to be output.

The processor 162 may be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments. The processor 162 is generally used to control the overall operation of the computer device 16. In this embodiment, the processor 162 is configured to execute computer readable instructions stored in the memory 161 or process data, such as computer readable instructions for executing the health assessment method.

The network interface 163 may include a wireless network interface or a wired network interface, and the network interface 163 is typically used to establish communication connections between the computer device 16 and other electronic devices.

In this embodiment, the influence data of the system in the knowledge base may be used to generate the health evaluation influenced by the target system to be tested for the user, so that the user may intuitively obtain the influence range of the target system to be tested, and may evaluate the influence of modification more accurately and more quickly according to the influence range of the target system to be tested, eliminate irrelevant interference points, simplify regression use cases, avoid that partial correlations are found to be not processed when the previous evaluation influence points are missed, and save development time and supplement logic when the previous evaluation influence points are together and the serious possible scheme design needs to override the remarked questions, thereby improving the efficiency of project development.

The present application also provides another embodiment, namely, a computer-readable storage medium storing computer-readable instructions executable by at least one processor to cause the at least one processor to perform the steps of the health assessment method as described above.

From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present application.

It is apparent that the above-described embodiments are only some embodiments of the present application, but not all embodiments, and the preferred embodiments of the present application are shown in the drawings, which do not limit the scope of the patent claims. This application may be embodied in many different forms, but rather, embodiments are provided in order to provide a thorough and complete understanding of the present disclosure. Although the application has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described in the foregoing description, or equivalents may be substituted for elements thereof. All equivalent structures made by the content of the specification and the drawings of the application are directly or indirectly applied to other related technical fields, and are also within the scope of the application.

Claims

1. A method of health assessment comprising the steps of:

2. The method of claim 1, wherein prior to the step of obtaining questionnaire data for a user, the method further comprises:

3. The health assessment method according to claim 2, wherein the step of determining the assessment item of the user to be assessed specifically comprises:

acquiring crowd characteristics of the user to be evaluated;

4. The method for health assessment according to claim 2, wherein said step of transmitting said assessment questionnaire to said user to be assessed to obtain questionnaire data of said user to be assessed, specifically comprises:

5. The method of claim 4, wherein the step of determining a next question of the assessment questionnaire based on the completed question and an answer to the completed question, specifically comprises:

6. The method according to any one of claims 1 to 5, wherein the step of determining an evaluation model of the user to be evaluated based on the questionnaire data specifically comprises:

7. The method according to any one of claims 1 to 5, characterized in that, after the step of determining the health evaluation result of the user to be evaluated based on the questionnaire data and the evaluation model, the method further comprises:

8. A health assessment device, comprising:

the acquisition module is used for acquiring questionnaire data of the user to be evaluated, wherein the questionnaire data is generated after the user to be evaluated fills out an evaluation questionnaire, and the questions of the evaluation questionnaire are dynamically adjusted according to the above semantics filled out by the user to be evaluated;

9. A computer device comprising a memory having stored therein computer readable instructions which when executed by a processor implement the steps of the health assessment method of any of claims 1 to 7.

10. A computer readable storage medium, characterized in that it has stored thereon computer readable instructions which, when executed by a processor, implement the steps of the health assessment method according to any of claims 1 to 7.