Method, device and equipment for acquiring health management plan based on health evaluation result
By using an automated artificial intelligence model based on health assessment results to generate personalized health management plans, the problem of cumbersome and inefficient acquisition processes in existing technologies has been solved, and efficient and reliable health management plan generation has been achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- KANG JIAN INFORMATION TECH (SHENZHEN) CO LTD
- Filing Date
- 2026-01-15
- Publication Date
- 2026-05-01
AI Technical Summary
The current process of accessing health management programs is cumbersome, relies on manual methods, and is therefore inefficient and susceptible to human intervention.
By acquiring the health data and assessment results of preset users, and using artificial intelligence models for training and evaluation, personalized health management plans are automatically generated.
It improves the efficiency of accessing health management plans, reduces access time, enhances the reliability of plans, and avoids the impact of human intervention.
Smart Images
Figure CN121964043A_ABST
Abstract
Description
Methods, devices, and equipment for obtaining health management plans based on health assessment results Technical Field
[0001] This invention relates to the field of artificial intelligence technology and can be applied to the field of smart healthcare. In particular, this invention relates to a method, apparatus, and equipment for obtaining health management plans based on health assessment results. Background Technology
[0002] In daily life, unhealthy eating habits, insufficient exercise, and chronic sleep deprivation are common, increasing the risk of chronic diseases. Health management plans can proactively identify these potential risks, guide users to develop healthy habits, maintain a positive and optimistic mindset, enhance psychological resilience, and better cope with various challenges.
[0003] However, the current process of obtaining health management plans for users is cumbersome, hindering the improvement of acquisition efficiency. This is because existing technologies often rely on manual methods to obtain users' health management plans. This process typically requires in-depth face-to-face communication between professionals and users, combining general health management principles with specific needs. This consumes a significant amount of time and effort to develop a health management plan, increasing the acquisition time and making it susceptible to human intervention. Therefore, it is detrimental to improving the efficiency of health management plan acquisition. Summary of the Invention
[0004] This invention provides a method, apparatus, computer equipment, and storage medium for obtaining health management plans based on health assessment results, in order to solve the technical problem that the current process of obtaining health management plans for users is cumbersome and not conducive to improving the efficiency of obtaining health management plans.
[0005] Firstly, a method for obtaining a health management plan based on health assessment results is provided, including: acquiring the health data and health assessment results of a preset user; forming training samples from the preset user's health data and health assessment results, forming a dataset from different training samples, and dividing the dataset into a training set and a test set; training an artificial intelligence model using the training set and obtaining the loss value of the artificial intelligence model on the training set; selecting the trained artificial intelligence model as a health assessment model when the loss value meets the convergence condition; obtaining the performance evaluation value of the health assessment model on the test set; and processing the current user's health data through the health assessment model when the performance evaluation value meets the evaluation condition to obtain the current user's health assessment result, and determining the current user's health management plan based on the current user's health assessment result. Further, the step of forming training samples from the preset user's health data and health assessment results, forming a dataset from different training samples, and dividing the dataset into a training set and a test set includes: forming training samples from the preset user's health data and health assessment results, forming a dataset from different training samples; obtaining the partitioning ratio from a configuration file, and dividing the dataset into a training set and a test set according to the partitioning ratio.
[0006] Furthermore, the step of training the artificial intelligence model using a training set and obtaining the loss value of the artificial intelligence model on the training set includes: loading the artificial intelligence model and training the artificial intelligence model using a training set; during the training process of the artificial intelligence model, obtaining the loss value of the artificial intelligence model on the training set through a preset loss function, wherein the loss function includes one or a combination of cross-entropy loss function and absolute loss function.
[0007] Furthermore, the step of selecting the trained artificial intelligence model as the health assessment model when the loss value meets the convergence condition includes: stopping the training of the artificial intelligence model when the loss value is less than a preset value; saving the trained artificial intelligence model; and selecting the trained artificial intelligence model as the health assessment model.
[0008] Furthermore, obtaining the performance evaluation value of the health assessment model on the test set includes: calling the input interface of the health assessment model, inputting the test set into the health assessment model through the input interface; and processing the test set through the health assessment model to obtain the performance evaluation value of the health assessment model on the test set.
[0009] Furthermore, when the performance evaluation value meets the evaluation conditions, the current user's health data is processed through the health assessment model to obtain the current user's health assessment result, and the current user's health management plan is determined based on the current user's health assessment result. This includes: when the performance evaluation value is greater than a preset evaluation value, acquiring the current user's health data, inputting the current user's health data into the health assessment model, processing the current user's health data through the health assessment model to obtain the current user's health assessment result; acquiring the dietary recommendations, exercise plan, medication management information, and regular physical examination information corresponding to the current user's health assessment result, writing the dietary recommendations, exercise plan, medication management information, and regular physical examination information corresponding to the current user's health assessment result into a preset template to obtain the current user's health management plan.
[0010] Furthermore, when the performance evaluation value meets the evaluation conditions, the health data of the current user is processed through the health evaluation model to obtain the health evaluation result of the current user, and the health management plan of the current user is determined based on the health evaluation result of the current user, the method for obtaining the health management plan includes: storing the health data of the current user, the health evaluation result of the current user and the health management plan into a target file, and creating an access interface for the target file.
[0011] Furthermore, after the health data of the current user is processed by the health assessment model to obtain the health assessment result of the current user when the performance evaluation value meets the assessment conditions, and the health management plan of the current user is determined based on the health assessment result of the current user, the method for obtaining the health management plan includes: creating a display window and displaying the health management plan through the display window.
[0012] Secondly, a device for obtaining a health management plan based on health assessment results is provided, comprising: a first acquisition module for acquiring health data and health assessment results of a preset user; a composition module for assembling the health data and health assessment results of the preset user into training samples, assembling different training samples into a dataset, and dividing the dataset into a training set and a test set; a second acquisition module for training an artificial intelligence model using the training set and acquiring the loss value of the artificial intelligence model on the training set; an evaluation module for selecting the trained artificial intelligence model as a health assessment model when the loss value meets the convergence condition; a third acquisition module for acquiring the performance evaluation value of the health assessment model on the test set; and a management module for processing the current user's health data through the health assessment model to obtain the current user's health assessment result when the performance evaluation value meets the evaluation condition, and determining the current user's health management plan based on the current user's health assessment result. Thirdly, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described health management plan acquisition method.
[0013] This application provides a method, apparatus, and equipment for obtaining health management plans based on health assessment results. The advantages are twofold: First, when the performance evaluation value meets the evaluation conditions, the current user's health data is processed through a health assessment model to obtain the current user's health assessment results. Based on these results, the current user's health management plan is determined. Since no manual acquisition is required, the time for obtaining the current user's health management plan is reduced, thus improving the efficiency of obtaining the current user's health management plan. Second, since it is not affected by human intervention, it helps to improve the reliability of the current user's health management plan. Attached Figure Description
[0014] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0015] Figure 1 is a schematic diagram of an application environment for a health management plan acquisition method according to an embodiment of the present invention; Figure 2 is a flowchart of a health management plan acquisition method according to an embodiment of the present invention; Figure 3 is a flowchart of a specific implementation of step S23 in Figure 2; Figure 4 is a flowchart of a specific implementation of step S25 in Figure 2; Figure 5 is a flowchart of a specific implementation of step S26 in Figure 2; Figure 6 is a structural schematic diagram of a health management plan acquisition device according to an embodiment of the present invention; Figure 7 is a structural schematic diagram of a computer device according to an embodiment of the present invention; Figure 8 is another structural schematic diagram of a computer device according to an embodiment of the present invention. Detailed Implementation
[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0017] Please refer to Figure 1. Figure 1 is a schematic diagram of an application environment for a health management plan acquisition method according to an embodiment of the present invention. The health management plan acquisition method provided by the embodiment of the present invention can be applied in the application environment shown in Figure 1, wherein the client communicates with the server through the network.
[0018] The server obtains the health data and health assessment results of preset users from the client; it then uses these data and results to form training samples, and combines different training samples into a dataset, which is further divided into a training set and a test set; the server trains the artificial intelligence model using the training set and obtains the loss value of the model on the training set; when the loss value meets the convergence condition, the trained artificial intelligence model is selected as the health assessment model; the server obtains the performance evaluation value of the health assessment model on the test set; when the performance evaluation value meets the evaluation condition, the server processes the current user's health data using the health assessment model to obtain the current user's health assessment result, and determines the current user's health management plan based on the result. The beneficial effects of the above-mentioned health management plan acquisition method, device, equipment, and medium are twofold. First, when the performance evaluation value meets the evaluation conditions, the current user's health data is processed through the health assessment model to obtain the current user's health assessment result. Based on the current user's health assessment result, the current user's health management plan is determined. Since no manual acquisition is required, the acquisition time of the current user's health management plan is reduced, which is conducive to improving the acquisition efficiency of the current user's health management plan. Second, since it is not affected by human intervention, it is conducive to improving the reliability of the current user's health management plan.
[0019] The device running the client is referred to as the client device.
[0020] Among them, the equipment that runs the server is referred to as: server equipment.
[0021] The client devices may include, but are not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices.
[0022] The server-side equipment can be implemented using a standalone server or a server cluster consisting of multiple servers. The invention will now be described in detail through specific embodiments.
[0023] Please refer to Figure 2, which is a flowchart of a health management plan acquisition method provided by an embodiment of the present invention, including the following steps: S21, acquiring the health data and health assessment results of a preset user; wherein, the health data of the preset user includes, but is not limited to, the physiological indicators, lifestyle data, and medical history of the preset user.
[0024] Among them, the physiological indicators of the preset users include, but are not limited to, the preset users' body temperature, blood pressure, heart rate, blood sugar level, and blood lipid level.
[0025] Among them, the preset user's lifestyle data includes, but is not limited to, the preset user's diet data, exercise data, and smoking data.
[0026] Among these, the smoking data of the preset users is a crucial set of information for comprehensively understanding their smoking behavior characteristics and health risks. This data includes the number of times the preset users smoke per week or month, and the number of years they have continued smoking since they started.
[0027] The preset user's medical history includes, but is not limited to, the types of diseases the preset user has and the year in which each disease was first diagnosed.
[0028] Among them, the preset user's medical history is a collection of detailed information about the preset user's past illnesses, which is a key basis for comprehensively assessing the preset user's health status.
[0029] There is a one-to-one correspondence between the health data of preset users and their health assessment results. Different preset users' health data correspond to different preset users' health assessment results.
[0030] For ease of explanation, the following example is provided: For instance, there is a preset user 1 and a preset user 2; the health data of preset user 1 corresponds to the health assessment results of preset user 1; the health data of preset user 2 corresponds to the health assessment results of preset user 2.
[0031] S22, The preset user's health data and preset user's health assessment results are used to form training samples, different training samples are used to form a dataset, and the dataset is divided into a training set and a test set; wherein, the step of using the preset user's health data and preset user's health assessment results to form training samples, different training samples are used to form a dataset, and the dataset is divided into a training set and a test set includes: using the preset user's health data and preset user's health assessment results to form training samples, different training samples are used to form a dataset; obtaining the partitioning ratio from the configuration file, and dividing the dataset into a training set and a test set according to the partitioning ratio.
[0032] S23, The AI model is trained using a training set to obtain the loss value of the AI model on the training set; In this case, the AI model is trained using a training set, and the rich and representative training samples in the training set enable the AI model to learn the characteristic patterns of different groups of people and various health conditions, thereby greatly improving the accuracy of health assessment.
[0033] S24, when the loss value meets the convergence condition, the trained artificial intelligence model is selected as the health assessment model; wherein, the step of selecting the trained artificial intelligence model as the health assessment model when the loss value meets the convergence condition includes: stopping the training of the artificial intelligence model when the loss value is less than a preset value; saving the trained artificial intelligence model; and selecting the trained artificial intelligence model as the health assessment model.
[0034] Among them, the trained artificial intelligence model is selected as the health assessment model. The health assessment model can quickly process massive amounts of health data and complete the health assessment of a large number of individuals in a short time, which greatly saves manpower and time costs, making large-scale health screening and real-time health monitoring possible.
[0035] S25, obtain the performance evaluation value of the health assessment model on the test set; the test set is a data sample set independent of the training set, and its data distribution is closer to the data in the actual application scenario, which can truly reflect the performance of the health assessment model when facing new data.
[0036] S26. When the performance evaluation value meets the evaluation conditions, the current user's health data is processed through the health evaluation model to obtain the current user's health evaluation result, and the current user's health management plan is determined based on the current user's health evaluation result.
[0037] Among them, health management programs are scientific and systematic intervention programs that aim to help current users improve their health status, reduce disease risk, and establish a sustainable healthy lifestyle through personalized strategies.
[0038] For ease of explanation, here is an example: For instance, the current user is user A. The health data of user A is processed through a health assessment model to obtain the health assessment results of user A. Based on the health assessment results of user A, a health management plan for user A is determined.
[0039] Among them, the current user's health data is the current user's health data.
[0040] Among them, the current user's health assessment result is the current user's health assessment result.
[0041] The current user's health data includes, but is not limited to, the current user's physiological indicators, the current user's lifestyle data, and the current user's medical history.
[0042] The current user's physiological indicators include, but are not limited to, the current user's body temperature, blood pressure, heart rate, blood sugar level, and blood lipid level.
[0043] The current user's lifestyle data includes, but is not limited to, the current user's diet data, exercise data, and smoking data.
[0044] Among these, current user smoking data is a crucial set of information for comprehensively understanding their smoking behavior characteristics and health risks. Current user smoking data includes the number of times the current user smokes per week or month, and the number of years the current user has continued smoking since they started.
[0045] The current user's medical history includes, but is not limited to, the types of diseases the current user has and the year in which each disease was first diagnosed.
[0046] Among them, the current user's medical history is a collection of detailed information about the current user's past illnesses, which is a key basis for comprehensively assessing the current user's health status.
[0047] There is a one-to-one correspondence between the current user's health data and the current user's health assessment results. Different current users' health data correspond to different current users' health assessment results.
[0048] For ease of explanation, here is an example: For instance, there is a current user 1 and a current user 2; the health data of current user 1 corresponds to the health assessment result of current user 1; the health data of current user 2 corresponds to the health assessment result of current user 2.
[0049] When the performance evaluation value meets the evaluation conditions, it means that the performance evaluation value of the health assessment model on the test set has reached the expected level, which means that the health assessment model can also give accurate and reliable health assessment results for the current user when faced with the current user's health data.
[0050] Wherein, when the performance evaluation value meets the evaluation conditions, the current user's health data is processed through the health evaluation model to obtain the current user's health evaluation result, and the current user's health management plan is determined based on the current user's health evaluation result, the health management plan acquisition method includes: storing the current user's health data, the current user's health evaluation result and the health management plan into a target file, and creating an access interface for the target file.
[0051] Wherein, when the performance evaluation value meets the evaluation conditions, the current user's health data is processed through the health evaluation model to obtain the current user's health evaluation result, and the current user's health management plan is determined based on the current user's health evaluation result, the health management plan acquisition method includes: creating a display window and displaying the health management plan through the display window.
[0052] In this embodiment of the invention, the beneficial effects are twofold. Firstly, when the performance evaluation value meets the evaluation conditions, the current user's health data is processed through the health assessment model to obtain the current user's health assessment result. Based on the current user's health assessment result, the current user's health management plan is determined. Since no manual acquisition is required, the acquisition time of the current user's health management plan is reduced, which is conducive to improving the acquisition efficiency of the current user's health management plan. Secondly, since it is not affected by human intervention, it is conducive to improving the reliability of the current user's health management plan.
[0053] Please refer to Figure 3. Figure 3 is a flowchart of a specific implementation of step S23 in Figure 2, which is described in detail below: S31, load the artificial intelligence model and train the artificial intelligence model using a training set; S32, during the training process of the artificial intelligence model, obtain the loss value of the artificial intelligence model on the training set through a preset loss function, wherein the loss function includes one or a combination of cross-entropy loss function and absolute loss function.
[0054] In this embodiment of the invention, the loss value is a direct feedback on the learning effect of the artificial intelligence model, reflecting the degree to which the artificial intelligence model fits the training set. By observing the changing trend of the loss value of the artificial intelligence model on the training set, the learning status of the artificial intelligence model can be determined.
[0055] Please refer to Figure 4, which is a flowchart of a specific implementation of step S25 in Figure 2, and is described in detail below: S41, call the input interface of the health assessment model, and input the test set into the health assessment model through the input interface; S42, process the test set through the health assessment model to obtain the performance evaluation value of the health assessment model on the test set.
[0056] In this embodiment of the invention, the performance evaluation value of the health assessment model on the test set can measure the generalization ability of the health assessment model on unseen data.
[0057] Please refer to Figure 5, which is a flowchart illustrating a specific implementation of step S26 in Figure 2, detailed as follows: S51, when the performance evaluation value is greater than the preset evaluation value, obtain the current user's health data, input the current user's health data into the health assessment model, process the current user's health data through the health assessment model, and obtain the current user's health assessment result; wherein, when the performance evaluation value is greater than the preset evaluation value, obtain the current user's health data, input the current user's health data into the health assessment model, process the current user's health data through the health assessment model, and obtain the current user's health assessment result, including: when the performance evaluation value is greater than the preset evaluation value, access the health management system, obtain the current user's health data from the health management system, input the current user's health data into the health assessment model, process the current user's health data through the health assessment model, and obtain the current user's health assessment result.
[0058] When the performance evaluation value is greater than the preset evaluation value, it means that the health assessment model's performance evaluation value on the test set exceeds expectations, which means that the health assessment model can also give accurate and reliable health assessment results for the current user when faced with the current user's health data.
[0059] S52: Obtain dietary recommendations, exercise plans, medication management information, and regular physical examination information corresponding to the current user's health assessment results; write the dietary recommendations, exercise plans, medication management information, and regular physical examination information corresponding to the current user's health assessment results into a preset template to obtain the current user's health management plan.
[0060] For ease of explanation, the following example is given: For instance, if the current user is user A, the health data of user A is processed through a health assessment model to obtain the health assessment results of user A. The model then retrieves the dietary recommendations, exercise plans, medication management information, and regular physical examination information corresponding to the health assessment results of user A. Finally, the model writes the dietary recommendations, exercise plans, medication management information, and regular physical examination information corresponding to the health assessment results of user A into a preset template to obtain the health management plan for user A.
[0061] In this embodiment of the invention, dietary recommendations, exercise plans, medication management information, and regular physical examination information corresponding to the current user's health assessment results are obtained. These information are then written into a preset template to obtain the current user's health management plan. Since no manual acquisition is required, the time for obtaining the health management plan is reduced, which helps to improve the efficiency of obtaining the health management plan.
[0062] Please refer to Figure 6, which is a structural schematic diagram of a health management plan acquisition device in an embodiment of the present invention. As shown in Figure 6, the health management plan acquisition device includes a first acquisition module 101, a component module 102, a second acquisition module 103, an evaluation module 104, a third acquisition module 105, and a management module 106. The functional modules are described in detail below: The first acquisition module 101 is used to acquire the health data and health assessment results of the preset users; the composition module 102 is used to compose the health data and health assessment results of the preset users into training samples, compose different training samples into a dataset, and divide the dataset into a training set and a test set; the second acquisition module 103 is used to train the artificial intelligence model using the training set and acquire the loss value of the artificial intelligence model on the training set; the evaluation module 104 is used to select the trained artificial intelligence model as the health assessment model when the loss value meets the convergence condition; the third acquisition module 105 is used to acquire the performance evaluation value of the health assessment model on the test set; the management module 106 is used to process the current user's health data through the health assessment model when the performance evaluation value meets the evaluation condition, obtain the current user's health assessment result, and determine the current user's health management plan based on the current user's health assessment result. In one embodiment, the component module 102 includes: a component subunit, used to combine the health data of preset users and the health assessment results of preset users into training samples, and to combine different training samples into a dataset; and a partitioning subunit, used to obtain the partitioning ratio from the configuration file, and to partition the dataset into a training set and a test set according to the partitioning ratio.
[0063] In one embodiment, the second acquisition module 103 includes: a loading subunit for loading an artificial intelligence model and training the artificial intelligence model using a training set; and an acquisition subunit for acquiring the loss value of the artificial intelligence model on the training set during the training process of the artificial intelligence model using a preset loss function, wherein the loss function includes one or a combination of cross-entropy loss function and absolute loss function.
[0064] In one embodiment, the evaluation module 104 includes: a stop subunit, used to stop training the artificial intelligence model when the loss value is less than a preset value; and a selection subunit, used to save the trained artificial intelligence model and select the trained artificial intelligence model as a health evaluation model.
[0065] In one embodiment, the third acquisition module 105 includes: a first input subunit, used to call the input interface of the health assessment model and input the test set into the health assessment model through the input interface; and an evaluation subunit, used to process the test set through the health assessment model and obtain the performance evaluation value of the health assessment model on the test set.
[0066] In one embodiment, the management module 106 includes: a second input subunit, used to acquire the current user's health data when the performance evaluation value is greater than a preset evaluation value, input the current user's health data into a health assessment model, process the current user's health data through the health assessment model, and obtain the current user's health assessment result; and a management subunit, used to acquire dietary recommendations, exercise plans, medication management information, and regular physical examination information corresponding to the current user's health assessment result, write the dietary recommendations, exercise plans, medication management information, and regular physical examination information corresponding to the current user's health assessment result into a preset template, and obtain the current user's health management plan.
[0067] In one embodiment, the health management plan acquisition device further includes: a storage module for storing the current user's health data, the current user's health assessment results, and the health management plan into a target file, and creating an access interface for the target file.
[0068] In one embodiment, the health management plan acquisition device further includes a display module for creating a display window and displaying the health management plan through the display window.
[0069] In this embodiment of the invention, the beneficial effects are twofold. Firstly, when the performance evaluation value meets the evaluation conditions, the current user's health data is processed through the health assessment model to obtain the current user's health assessment result. Based on the current user's health assessment result, the current user's health management plan is determined. Since no manual acquisition is required, the acquisition time of the current user's health management plan is reduced, which is conducive to improving the acquisition efficiency of the current user's health management plan. Secondly, since it is not affected by human intervention, it is conducive to improving the reliability of the current user's health management plan.
[0070] For specific limitations on the devices for obtaining health management plans, please refer to the limitations on the methods for obtaining health management plans mentioned above, which will not be repeated here.
[0071] The various modules in the aforementioned health management plan acquisition device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can invoke and execute the corresponding operations of each module.
[0072] Please refer to Figure 7, which is a structural schematic diagram of a computer device according to one embodiment of the present invention. In one embodiment, a computer device is provided, which may be a server device, and its internal structure diagram may be as shown in Figure 7. The computer device includes a processor, a memory, a network interface, and a database connected via a system bus.
[0073] The processor of this computer device provides computing and control capabilities. The memory of this computer device includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and databases. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. When the computer program is executed by the processor, it can implement the function or steps of a health management plan acquisition method based on health assessment results on the server device.
[0074] Please refer to Figure 8, which is another structural schematic diagram of a computer device according to one embodiment of the present invention. In one embodiment, a computer device is provided, which can be a client device, and its internal structure diagram is shown in Figure 8. The computer device includes a processor, memory, network interface, display screen, and input device connected via a system bus. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. When the computer program is executed by the processor, it can implement the function or steps of a health management plan acquisition method based on health assessment results on the client device.
[0075] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. It should be noted that the functions or steps achievable by the computer-readable storage medium or computer device described above can be found in the relevant descriptions in the foregoing method embodiments; to avoid repetition, they will not be described again here.
[0076] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), graphics processing units (GPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.
[0077] The methods and products (including but not limited to devices and equipment) disclosed in the embodiments herein can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some sub-samples may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms. Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to implement this embodiment according to actual needs. Furthermore, the functional units in the embodiments of this disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
[0078] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions. Furthermore, any software tools or components not belonging to this company that appear in the embodiments of this application are merely illustrative examples and do not represent actual use.
Claims
1. A method for obtaining a health management plan based on health assessment results, characterized in that, include: Obtain the health data and health assessment results of preset users; The health data and health assessment results of the preset users are used to form training samples. Different training samples are used to form a dataset. The dataset is divided into training set and test set. The AI model is trained using a training set, and the loss value of the AI model on the training set is obtained; when the loss value meets the convergence condition, the trained AI model is selected as the health assessment model. Obtain the performance evaluation value of the health assessment model on the test set; When the performance evaluation value meets the evaluation conditions, the current user's health data is processed through the health assessment model to obtain the current user's health assessment result, and the current user's health management plan is determined based on the current user's health assessment result.
2. The method for obtaining a health management plan according to claim 1, characterized in that, The step of forming training samples from the health data and health assessment results of preset users, forming datasets from different training samples, and dividing the datasets into training sets and test sets includes: forming training samples from the health data and health assessment results of preset users, forming datasets from different training samples; obtaining the partitioning ratio from the configuration file, and dividing the datasets into training sets and test sets according to the partitioning ratio.
3. The method for obtaining a health management plan according to claim 1, characterized in that, The step of training the artificial intelligence model using a training set and obtaining the loss value of the artificial intelligence model on the training set includes: loading the artificial intelligence model and training the artificial intelligence model using a training set; during the training process of the artificial intelligence model, obtaining the loss value of the artificial intelligence model on the training set through a preset loss function, wherein the loss function includes one or a combination of cross-entropy loss function and absolute loss function.
4. The method for obtaining a health management plan according to claim 1, characterized in that, The step of selecting the trained artificial intelligence model as the health assessment model when the loss value meets the convergence condition includes: stopping the training of the artificial intelligence model when the loss value is less than a preset value; saving the trained artificial intelligence model; and selecting the trained artificial intelligence model as the health assessment model.
5. The method for obtaining a health management plan according to claim 1, characterized in that, The process of obtaining the performance evaluation value of the health assessment model on the test set includes: calling the input interface of the health assessment model, inputting the test set into the health assessment model through the input interface; and processing the test set through the health assessment model to obtain the performance evaluation value of the health assessment model on the test set.
6. The method for obtaining a health management plan according to claim 1, characterized in that, When the performance evaluation value meets the evaluation conditions, the current user's health data is processed through a health assessment model to obtain the current user's health assessment result. Based on the current user's health assessment result, a health management plan for the current user is determined. This includes: when the performance evaluation value is greater than a preset evaluation value, acquiring the current user's health data, inputting the current user's health data into the health assessment model, processing the current user's health data through the health assessment model to obtain the current user's health assessment result; acquiring dietary recommendations, exercise plans, medication management information, and regular physical examination information corresponding to the current user's health assessment result, writing the dietary recommendations, exercise plans, medication management information, and regular physical examination information corresponding to the current user's health assessment result into a preset template to obtain the current user's health management plan.
7. The method for obtaining a health management plan according to any one of claims 1 to 6, characterized in that, When the performance evaluation value meets the evaluation conditions, the health data of the current user is processed through the health evaluation model to obtain the health evaluation result of the current user. After determining the health management plan of the current user based on the health evaluation result of the current user, the method for obtaining the health management plan includes: storing the health data of the current user, the health evaluation result of the current user and the health management plan into a target file, and creating an access interface for the target file.
8. The method for obtaining a health management plan according to any one of claims 1 to 6, characterized in that, When the performance evaluation value meets the evaluation conditions, the health data of the current user is processed by the health evaluation model to obtain the health evaluation result of the current user, and the health management plan of the current user is determined based on the health evaluation result of the current user, the method for obtaining the health management plan includes: creating a display window and displaying the health management plan through the display window.
9. A device for obtaining health management plans based on health assessment results, characterized in that, include: The first acquisition module is used to acquire the health data and health assessment results of the preset users. The component module is used to combine the health data and health assessment results of the preset users into training samples, combine different training samples into a dataset, and divide the dataset into a training set and a test set. The second acquisition module is used to train the artificial intelligence model using the training set and obtain the loss value of the artificial intelligence model on the training set. The evaluation module is used to select the trained artificial intelligence model as the health evaluation model when the loss value meets the convergence condition. The third acquisition module is used to acquire the performance evaluation value of the health assessment model on the test set; The management module is used to process the current user's health data through the health assessment model when the performance evaluation value meets the evaluation conditions, obtain the current user's health assessment result, and determine the current user's health management plan based on the current user's health assessment result.
10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the health management plan acquisition method as described in any one of claims 1 to 8.