A health treatment monitoring system based on dual medical tests

Abstract

The present invention discloses a health treatment monitoring system based on dual medical examinations. The present invention relates to the field of data monitoring, and includes a health treatment monitoring platform, which includes a data acquisition module, a data storage module, a data analysis module, a personalized analysis module, and a treatment optimization module; the data acquisition module is used to acquire biochemical examination data and imaging examination data; the data storage module stores the acquired data; the data analysis module is used to acquire physiological mapping signal data and imaging mapping signal data; the personalized analysis module is used to acquire personalized mapping data corresponding to a patient account; the treatment optimization module is used to perform health analysis on corresponding biochemical examination data and imaging examination data according to the personalized mapping data, and acquire corresponding optimized treatment plans; the present invention provides personalization and accuracy of health treatment to a certain extent.

Description

Technical Field

[0001] The invention relates to the field of data monitoring, and in particular to a health treatment monitoring system based on dual medical tests. Background Art

[0002] In modern healthcare management, early detection and continuous monitoring of diseases are important means to protect patients' health. Traditional health monitoring systems mostly rely on a single medical test method, which may have shortcomings in some cases. For example, a single test method may not be sensitive enough to the early signs of certain diseases, or may not work well in specific patient groups. In addition, a single test method may not fully reflect the patient's health status, because the complexity of the disease usually requires a comprehensive evaluation of multiple indicators.

[0003] In recent years, the medical field has gradually paid more attention to the dual testing method. This method can provide more comprehensive health information by combining two different testing technologies, thereby improving the detection rate and treatment effect of the disease; however, the health treatment of different patients needs to be optimized according to their own physical condition, and cannot be treated by a single standard. Therefore, how to perform personalized optimization treatment according to the patient's physical condition is a problem we need to solve. To this end, a health treatment monitoring system based on dual medical testing is now provided. Summary of the invention

[0004] In order to solve the above technical problems, the object of the present invention is to provide a health treatment monitoring system based on dual medical tests.

[0005] The object of the present invention can be achieved by the following technical solutions: A health treatment monitoring system based on dual medical examinations, comprising a health treatment monitoring platform, wherein the health treatment monitoring platform is communicatively connected with a data acquisition module, a data storage module, a data integration module, a data analysis module, a personalized analysis module and a treatment optimization module;

[0006] The data acquisition module is used to obtain the biochemical examination data and imaging examination data corresponding to the corresponding patient, and associate them with the corresponding patient account;

[0007] The data storage module is used to set a corresponding encryption key for the obtained data according to the patient account number, encrypt the obtained data according to the encryption key, and store it;

[0008] The data integration module is used to integrate the data associated with the patient account, obtain the patient treatment data according to the integration result, and send it to the data analysis module;

[0009] The data analysis module is used to perform standard mapping processing on the patient treatment data, obtain the physiological mapping signal data and image mapping signal data corresponding to the patient account, and mark the treatment time series;

[0010] The personalized analysis module is used to analyze and process the physiological mapping signal data and the image mapping signal data according to the treatment time sequence, and obtain the personalized mapping coefficient corresponding to the treatment time sequence of the patient account;

[0011] The treatment optimization module is used to perform health analysis on the biochemical examination data and imaging examination data obtained at the current moment according to the personalized mapping coefficient corresponding to the patient account treatment time series, and obtain an optimized treatment plan based on the analysis results.

[0012] Furthermore, the process of the data acquisition module acquiring the biochemical examination data and imaging examination data corresponding to the corresponding patient includes:

[0013] Setting up a user input unit, a biochemical detection unit and an image detection unit;

[0014] The user input unit is used to obtain patient data information and set up a patient account according to the patient data information;

[0015] The biochemical detection unit is used to obtain the physiological examination data corresponding to the patient according to the patient account;

[0016] The image detection unit is used to obtain the image examination data corresponding to the patient according to the patient account;

[0017] The acquired physiological examination data and imaging examination data are respectively marked according to the acquisition time and are associated with the corresponding patient accounts.

[0018] Furthermore, the data storage module sets a corresponding encryption key for the obtained data according to the patient account number, and the process of encrypting the obtained data according to the encryption key includes:

[0019] Setting up a data encryption unit and a data storage unit;

[0020] The data encryption unit obtains the patient data information corresponding to the patient account, and stores the data included in the corresponding patient account according to the patient data information;

[0021] Sort the data types corresponding to the patient data information by data size, set the data types in sequence to the coding mapping function according to the data size sorting result, and set the patient data information to the corresponding patient coding data based on the coding mapping function; set the obtained patient coding data to the patient coding data table, and obtain the encryption key corresponding to the patient account based on the patient coding data table;

[0022] Using the obtained encryption key to encrypt the data obtained in the patient account;

[0023] The data storage unit is used to store data that is mutually associated with the patient account and has been encrypted according to the patient account, and to set a data storage link according to the patient account, and to set a corresponding data storage space segment on the data storage link according to demand to store the corresponding data.

[0024] Furthermore, the data integration module integrates the data associated with the patient account, and the process of obtaining the patient treatment data according to the integration result includes:

[0025] Set up data comparison unit and data integration unit;

[0026] The data comparison unit is used to be associated with the corresponding data storage space segment in the data storage module, wherein a platform dynamic public key is provided, which is used to decrypt the data in the data storage space segment and isolate it from the corresponding patient data information, obtain the corresponding physiological examination data and imaging examination data in each data storage space in the data storage module, set the data stored in the data storage module to the medical diagnosis and treatment map of the corresponding department, compare and analyze the entered data with the corresponding medical diagnosis and treatment map, and judge whether the entered data belongs to the corresponding medical diagnosis and treatment map according to the comparison and analysis results. If so, obtain its position information in the medical diagnosis and treatment map; if not, mark the entered data as abnormal data;

[0027] The data integration unit obtains the data stored in the corresponding data storage space segments of each patient account, marks the analysis results in each data storage space segment in the data storage space corresponding to the patient account, sets the data in the data storage space segment corresponding to the marked result as patient treatment data, and sends it to the data analysis module.

[0028] Furthermore, the process of obtaining the physiological mapping signal data corresponding to the patient account includes:

[0029] The data analysis module obtains the patient treatment data corresponding to the patient account, obtains the physiological detection data and the imaging detection data of the corresponding data storage space segment according to the patient treatment data, and sets the treatment time sequence according to the data storage space segment and the acquisition time to which it belongs;

[0030] Obtaining the data type of the physiological detection data in each treatment time series, setting the corresponding longitudinal unit part according to the data type, sequentially arranging the longitudinal unit parts, setting the scaling ratio of the corresponding longitudinal unit part according to the data type, mapping the physiological detection data of the corresponding data type to the longitudinal unit part according to the scaling ratio, and obtaining the physiological detection curve corresponding to the physiological detection data of the corresponding data type in the longitudinal unit part;

[0031] Performing Fourier transformation on the physiological detection curve corresponding to each longitudinal unit part to obtain the physiological detection signal, performing standard mapping processing on the obtained physiological detection signal to obtain corresponding curve approximation data and curve detail data, and performing mapping marking in the corresponding physiological detection curve;

[0032] The mapping labeling result of the physiological detection curve corresponding to each longitudinal unit part is set as the physiological mapping signal data corresponding to the patient account.

[0033] Furthermore, the process of obtaining the image mapping signal data corresponding to the patient account includes:

[0034] Obtain the image detection data in each treatment time series of the patient account, perform grayscale processing on each image detection data in turn to obtain a grayscale image, perform segmentation processing on each grayscale image based on an edge detection algorithm, and obtain multiple regional grayscale images corresponding to the corresponding grayscale image;

[0035] The image detection data is set to a corresponding image management space according to its data type, and a corresponding longitudinal unit part is set in the image management space according to the regional grayscale image, and the disease feature is extracted from the regional grayscale image corresponding to each longitudinal unit part to obtain a regional disease signal, and the regional disease signal is mapped into the regional grayscale image;

[0036] The mapping marking result of the grayscale image of the area corresponding to each longitudinal unit part in each image management space is set as the image mapping signal data corresponding to the patient account.

[0037] Furthermore, the process of obtaining the personalized mapping coefficient corresponding to the treatment time series of the patient account includes:

[0038] Acquire physiological mapping signal data and image mapping signal data corresponding to the corresponding longitudinal unit parts in sequence according to the treatment time sequence, and set the data corresponding to the longitudinal unit parts corresponding to the same data type as mapping signal data sets in sequence according to the treatment time sequence;

[0039] Analyze and process the data in the mapping signal data set corresponding to each longitudinal unit part in turn, analyze and process the data in each mapping signal data set based on Fourier transform, and obtain the frequency domain coefficients and phase coefficients corresponding to adjacent treatment time series in turn;

[0040] All frequency domain coefficients and phase coefficients in each mapping signal data set are analyzed and processed to obtain personalized mapping coefficients corresponding to the corresponding longitudinal unit parts, and send them to the treatment optimization module.

[0041] Furthermore, the process of the treatment optimization module obtaining the optimized treatment plan includes:

[0042] Obtain the physiological test data, imaging test data and personalized mapping coefficients corresponding to the corresponding longitudinal unit parts of the patient account, analyze and process the obtained physiological test data and imaging test data with the corresponding personalized mapping coefficients respectively, obtain the corresponding health assessment data, comprehensively process the health assessment data of each longitudinal unit part in turn, and set a corresponding optimized treatment plan according to the comprehensive processing results.

[0043] Compared with the prior art, the beneficial effects of the present invention are: by analyzing and processing different types of physiological detection data and image detection data, by analyzing the corresponding physiological mapping signal data and image mapping signal data, personalized mapping data of different types of data information of corresponding patients are obtained according to the physiological mapping signal data and image mapping signal data, thereby reflecting the personalized physical condition of the corresponding patients, and setting the corresponding optimized treatment plan according to the corresponding personalized physical condition of the patients, thereby increasing the accuracy of the optimized treatment plan to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a schematic diagram of a health treatment monitoring system based on dual medical tests according to an embodiment of the present application. DETAILED DESCRIPTION

[0045] like Figure 1 As shown, a health treatment monitoring system based on dual medical examinations includes a health treatment monitoring platform, wherein the health treatment monitoring platform is communicatively connected with a data acquisition module, a data storage module, a data sharing module, a data analysis module, a personalized analysis module and a treatment optimization module;

[0046] The health treatment monitoring platform is used to monitor and analyze the data of patients during rehabilitation treatment;

[0047] The data acquisition module is used to obtain the biochemical examination data and imaging examination data corresponding to the corresponding patient, and associate it with the corresponding patient account. The specific implementation process includes:

[0048] Setting up a user input unit, a biochemical detection unit and an image detection unit;

[0049] The user input unit is used to obtain patient data information and set up a patient account according to the patient data information, wherein the patient data information includes the patient's basic information, medical history information and living habit information;

[0050] The patient's basic information includes name, gender, age, ID number and contact information;

[0051] Medical history information included family history, personal medical history, and allergies;

[0052] Lifestyle information includes smoking, drinking, eating, and exercise habits;

[0053] The biochemical detection unit is used to obtain the physiological examination data corresponding to the patient according to the patient account, wherein the physiological examination data includes blood test data, urine test data, biochemical index data and electrocardiogram test data, etc.;

[0054] The image detection unit is used to obtain the image examination data corresponding to the patient according to the patient account, wherein the image detection data includes X-ray examination images, CT examination images, ultrasound examination images, MRI image detection images, etc.;

[0055] The acquired physiological examination data and imaging examination data are respectively marked according to the acquisition time, and are associated with the corresponding patient accounts;

[0056] It should be further explained that, in the specific implementation process, the patient data information, physiological examination data and imaging examination data obtained by the data acquisition module need to include one of the types, and it is not necessary to collect every type of data.

[0057] The data storage module is used to set a corresponding encryption key for the obtained data according to the patient account, encrypt the obtained data according to the encryption key, and store it. The specific implementation process includes:

[0058] Setting up a data encryption unit and a data storage unit;

[0059] The data encryption unit obtains the patient data information corresponding to the patient account, and stores the data included in the corresponding patient account according to the patient data information;

[0060] The data types corresponding to the patient data information are sorted by data size, and the data types are sequentially set with coding mapping functions according to the data size sorting results, and the patient data information is set with corresponding patient coding data based on the coding mapping function. The specific implementation process includes:

[0061] Get the corresponding data type for numerical conversion, and get the mean value corresponding to the corresponding data type according to the numerical conversion result and standard deviation , maps the data type to standard normal distribution data with a mean of 0 and a standard deviation of 1 ,in, ;

[0062] The obtained standard normal distribution data are sorted in order according to the data size corresponding to the data type, and the coding characters are converted to obtain the corresponding patient coding data;

[0063] The obtained patient coding data is set in a patient coding data table, and an encryption key corresponding to the patient account is obtained based on the patient coding data table;

[0064] Using the obtained encryption key to encrypt the data obtained in the patient account;

[0065] The data storage unit is used to store data that is mutually associated with the patient account and has been encrypted according to the patient account, and to set a data storage link according to the patient account, and to set a corresponding data storage space segment on the data storage link according to demand to store the corresponding data.

[0066] The data integration module is used to integrate the data associated with the patient account, obtain the patient treatment data according to the integration result, and send it to the data analysis module. The specific implementation process includes:

[0067] Set up data comparison unit and data integration unit;

[0068] The data comparison unit is used to be associated with the corresponding data storage space segment in the data storage module, wherein a platform dynamic public key is provided, and the platform dynamic public key is used to obtain the physiological examination data and image detection data stored in each data storage space segment within the corresponding time period, and decrypt the same, wherein the decryption process is not associated with the patient data information, and is isolated from the corresponding patient data information, and obtains the corresponding physiological examination data and image examination data in each data storage space in the data storage module;

[0069] The data stored in the data storage module are set to the medical diagnosis and treatment map of the corresponding department, and the entered data is compared and analyzed with the corresponding medical diagnosis and treatment map. According to the comparison and analysis results, it is determined whether the entered data belongs to the corresponding medical diagnosis and treatment map. If it does, its position information in the medical diagnosis and treatment map is obtained; if it does not, the entered data is marked as abnormal data; the data marked as abnormal is sent to the corresponding medical staff for analysis and processing to determine whether the corresponding data information is entered into the medical diagnosis and treatment map;

[0070] The data integration unit obtains the data stored in the corresponding data storage space segments of each patient account, marks the analysis results in each data storage space segment in the data storage space corresponding to the patient account, sets the data in the data storage space segment corresponding to the marked result as patient treatment data, and sends it to the data analysis module.

[0071] The data analysis module is used to perform standard mapping processing on the patient treatment data, obtain the physiological mapping signal data and image mapping signal data corresponding to the patient account, and mark the treatment time series. The specific implementation process includes:

[0072] The data analysis module obtains the patient treatment data corresponding to the patient account, obtains the physiological detection data and the imaging detection data of the corresponding data storage space segment according to the patient treatment data, and sets the treatment time sequence according to the data storage space segment and the acquisition time to which it belongs;

[0073] Obtaining the data type of the physiological detection data in each treatment time series, setting the corresponding longitudinal unit part according to the data type, sequentially arranging the longitudinal unit parts, setting the scaling ratio of the corresponding longitudinal unit part according to the data type, mapping the physiological detection data of the corresponding data type to the longitudinal unit part according to the scaling ratio, and obtaining the physiological detection curve corresponding to the physiological detection data of the corresponding data type in the longitudinal unit part;

[0074] Performing Fourier transformation on the physiological detection curves corresponding to each longitudinal unit part to obtain the physiological detection signal, the specific implementation process includes:

[0075] The physiological detection data corresponding to the physiological detection curve is marked as , the frequency domain signal corresponding to the physiological detection curve is marked as , the length of the physiological detection curve is marked as N, and its frequency is marked as f, where:

[0076] ;

[0077] Performing standard mapping processing on the obtained physiological detection signal, obtaining corresponding curve approximation data and curve detail data, and making mapping marks in the corresponding physiological detection curve;

[0078] The mapping mark result of the physiological detection curve corresponding to each longitudinal unit part is set as the physiological mapping signal data corresponding to the patient account;

[0079] Obtain the image detection data in each treatment time series of the patient account, perform grayscale processing on each image detection data in turn to obtain a grayscale image, perform segmentation processing on each grayscale image based on an edge detection algorithm, and obtain multiple regional grayscale images corresponding to the corresponding grayscale image;

[0080] The image detection data is set to a corresponding image management space according to its data type, and a corresponding longitudinal unit part is set in the image management space according to the regional grayscale image, and the disease feature is extracted from the regional grayscale image corresponding to each longitudinal unit part to obtain a regional disease signal, and the regional disease signal is mapped into the regional grayscale image;

[0081] The mapping marking result of the grayscale image of the area corresponding to each longitudinal unit part in each image management space is set as the image mapping signal data corresponding to the patient account.

[0082] The personalized analysis module is used to analyze and process the physiological mapping signal data and the image mapping signal data according to the treatment time sequence, and obtain the personalized mapping coefficient corresponding to the treatment time sequence of the patient account. The specific implementation process includes:

[0083] Acquire physiological mapping signal data and image mapping signal data corresponding to the corresponding longitudinal unit parts in sequence according to the treatment time sequence, and set the data corresponding to the longitudinal unit parts corresponding to the same data type as mapping signal data sets in sequence according to the treatment time sequence;

[0084] Analyze and process the data in the mapping signal data set corresponding to each longitudinal unit part in turn, analyze and process the data in each mapping signal data set based on Fourier transform, and obtain the frequency domain coefficients and phase coefficients corresponding to adjacent treatment time series in turn;

[0085] All frequency domain coefficients and phase coefficients in each mapping signal data set are analyzed and processed to obtain personalized mapping coefficients corresponding to the corresponding longitudinal unit parts, and send them to the treatment optimization module.

[0086] The treatment optimization module is used to perform health analysis on the biochemical examination data and imaging examination data obtained at the current moment according to the personalized mapping coefficient corresponding to the treatment time series of the patient account, and obtain an optimized treatment plan according to the analysis results. The specific implementation process includes:

[0087] Obtain the physiological test data, imaging test data and personalized mapping coefficients corresponding to the corresponding longitudinal unit parts of the patient account, analyze and process the obtained physiological test data and imaging test data with the corresponding personalized mapping coefficients respectively, obtain the corresponding health assessment data, comprehensively process the health assessment data of each longitudinal unit part in turn, and set a corresponding optimized treatment plan according to the comprehensive processing results.

[0088] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A health treatment monitoring system based on dual medical examinations, including a health treatment monitoring platform, characterized in that: The health treatment monitoring platform is communicatively connected with a data acquisition module, a data storage module, a data integration module, a data analysis module, a personalized analysis module and a treatment optimization module; The data acquisition module is used to obtain the biochemical examination data and imaging examination data corresponding to the corresponding patient, and associate them with the corresponding patient account; The data storage module is used to set a corresponding encryption key for the obtained data according to the patient account number, encrypt the obtained data according to the encryption key, and store it; The data integration module is used to integrate the data associated with the patient account, obtain the patient treatment data according to the integration result, and send it to the data analysis module; The data analysis module is used to perform standard mapping processing on the patient treatment data, obtain the physiological mapping signal data and image mapping signal data corresponding to the patient account, and mark the treatment time series; The process of obtaining the physiological mapping signal data corresponding to the patient account includes: The data analysis module obtains the patient treatment data corresponding to the patient account, obtains the physiological detection data and the imaging detection data of the corresponding data storage space segment according to the patient treatment data, and sets the treatment time sequence according to the data storage space segment and the acquisition time to which it belongs; Obtaining the data type of the physiological detection data in each treatment time series, setting the corresponding longitudinal unit part according to the data type, sequentially arranging the longitudinal unit parts, setting the scaling ratio of the corresponding longitudinal unit part according to the data type, mapping the physiological detection data of the corresponding data type to the longitudinal unit part according to the scaling ratio, and obtaining the physiological detection curve corresponding to the physiological detection data of the corresponding data type in the longitudinal unit part; Performing Fourier transformation on the physiological detection curve corresponding to each longitudinal unit part to obtain the physiological detection signal, performing standard mapping processing on the obtained physiological detection signal to obtain corresponding curve approximation data and curve detail data, and performing mapping marking in the corresponding physiological detection curve; The mapping mark result of the physiological detection curve corresponding to each longitudinal unit part is set as the physiological mapping signal data corresponding to the patient account; The process of obtaining the image mapping signal data corresponding to the patient account includes: Obtain the image detection data in each treatment time series of the patient account, perform grayscale processing on each image detection data in turn to obtain a grayscale image, perform segmentation processing on each grayscale image based on an edge detection algorithm, and obtain multiple regional grayscale images corresponding to the corresponding grayscale image; The image detection data is set to a corresponding image management space according to its data type, and a corresponding longitudinal unit part is set in the image management space according to the regional grayscale image, and the disease feature is extracted from the regional grayscale image corresponding to each longitudinal unit part to obtain a regional disease signal, and the regional disease signal is mapped into the regional grayscale image; The mapping mark result of the grayscale image of the area corresponding to each longitudinal unit part in each image management space is set as the image mapping signal data corresponding to the patient account; The personalized analysis module is used to analyze and process the physiological mapping signal data and the image mapping signal data according to the treatment time sequence, and obtain the personalized mapping coefficient corresponding to the treatment time sequence of the patient account; The process of obtaining the personalized mapping coefficient corresponding to the treatment time series of the patient account includes: Acquire physiological mapping signal data and image mapping signal data corresponding to the corresponding longitudinal unit parts in sequence according to the treatment time sequence, and set the data corresponding to the longitudinal unit parts corresponding to the same data type as mapping signal data sets in sequence according to the treatment time sequence; Analyze and process the data in the mapping signal data set corresponding to each longitudinal unit part in turn, analyze and process the data in each mapping signal data set based on Fourier transform, and obtain the frequency domain coefficients and phase coefficients corresponding to adjacent treatment time series in turn; Analyze and process all frequency domain coefficients and phase coefficients in each mapping signal data set, obtain personalized mapping coefficients corresponding to the corresponding longitudinal unit part, and send them to the treatment optimization module; The treatment optimization module is used to perform health analysis on the biochemical examination data and imaging examination data obtained at the current moment according to the personalized mapping coefficient corresponding to the patient account treatment time series, and obtain an optimized treatment plan based on the analysis results.

2. A health treatment monitoring system based on dual medical tests according to claim 1, characterized in that: The process of the data acquisition module acquiring the biochemical examination data and imaging examination data corresponding to the corresponding patient includes: Setting up a user input unit, a biochemical detection unit and an image detection unit; The user input unit is used to obtain patient data information and set up a patient account according to the patient data information; The biochemical detection unit is used to obtain the physiological examination data corresponding to the patient according to the patient account; The image detection unit is used to obtain the image examination data corresponding to the patient according to the patient account; The acquired physiological examination data and imaging examination data are respectively marked according to the acquisition time and are associated with the corresponding patient accounts.

3. A health treatment monitoring system based on dual medical tests according to claim 2, characterized in that: The data storage module sets a corresponding encryption key for the obtained data according to the patient account number, and the process of encrypting the obtained data according to the encryption key includes: Setting up a data encryption unit and a data storage unit; The data encryption unit obtains the patient data information corresponding to the patient account, and stores the data included in the corresponding patient account according to the patient data information; Sort the data types corresponding to the patient data information by data size, set the data types in sequence to the coding mapping function according to the data size sorting result, and set the patient data information to the corresponding patient coding data based on the coding mapping function; set the obtained patient coding data to the patient coding data table, and obtain the encryption key corresponding to the patient account based on the patient coding data table; Using the obtained encryption key to encrypt the data obtained in the patient account; The data storage unit is used to store data that is mutually associated with the patient account and has been encrypted according to the patient account, and to set a data storage link according to the patient account, and to set a corresponding data storage space segment on the data storage link according to demand to store the corresponding data.

4. A health treatment monitoring system based on dual medical tests according to claim 3, characterized in that: The data integration module integrates the data associated with the patient account and obtains the patient treatment data according to the integration result, including: Set up a data integration unit; The data integration unit obtains the data stored in the corresponding data storage space segments of each patient account, marks the analysis results in each data storage space segment in the data storage space corresponding to the patient account, sets the data in the data storage space segment corresponding to the marked result as patient treatment data, and sends it to the data analysis module.

5. A health treatment monitoring system based on dual medical tests according to claim 4, characterized in that: The process of obtaining the optimized treatment plan by the treatment optimization module includes: Obtain the physiological test data, imaging test data and personalized mapping coefficients corresponding to the corresponding longitudinal unit parts of the patient account, analyze and process the obtained physiological test data and imaging test data with the corresponding personalized mapping coefficients respectively, obtain the corresponding health assessment data, comprehensively process the health assessment data of each longitudinal unit part in turn, and set a corresponding optimized treatment plan according to the comprehensive processing results.

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