CN117951190A

CN117951190A - Human body index abnormal data processing method and system based on artificial intelligence

Info

Publication number: CN117951190A
Application number: CN202410303318.0A
Authority: CN
Inventors: 陈鹰; 王曦; 楚秀娟
Original assignee: Shenzhen Sonka Electronic Medical Co ltd
Current assignee: Shenzhen Sonka Electronic Medical Co ltd
Priority date: 2024-03-18
Filing date: 2024-03-18
Publication date: 2024-04-30
Anticipated expiration: 2044-03-18
Also published as: CN117951190B

Abstract

The application discloses a human body index abnormal data processing method and system based on artificial intelligence, wherein the method comprises the following steps: acquiring a request video shot by a user side application program in a monitoring mode, wherein the request video comprises image information of a requester and description voice information of the requester on the self condition; identifying the image information of the requester, and extracting the historical physical examination information of the requester stored in a management platform database; updating corresponding data of the historical physical examination information based on the obtained current information to obtain current data information; processing the descriptive voice information of the requester to obtain key semantics; generating a requester data table based on the current data information and the key semantics; processing the requester data table to obtain abnormal data of the requester; based on the anomaly data of the requester, a physical examination package is recommended to the requester. The application aims to solve the technical problem that physical examination data management does not have flexibility and convenience.

Description

Human body index abnormal data processing method and system based on artificial intelligence

Technical Field

The application relates to the technical field of intelligent monitoring, in particular to a human index abnormal data processing method and system based on artificial intelligence.

Background

Physical examination refers to the performance of a series of examinations and tests on the body to assess the health of an individual and to find potential health problems. Therefore, it is important to maintain personal health to go to a hospital or a professional physical examination place for physical examination at regular intervals.

However, there are often limitations in the management and tracking of existing physical examination data. For example, for those who frequently replace cities or living places for work or other reasons, due to inflexibility and convenience in data management, they cannot acquire own body abnormality data in time, thereby missing the best opportunity for early intervention and treatment.

The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present application and is not intended to represent an admission that the foregoing is prior art.

Disclosure of Invention

The application mainly aims to provide a human index abnormal data processing method and system based on artificial intelligence, and aims to solve the technical problem that physical examination data management does not have flexibility and convenience.

In order to achieve the above object, the present application provides a human body index abnormal data processing method based on artificial intelligence, the method comprising: acquiring a request video shot by a user side application program in a monitoring mode, wherein the request video comprises image information of a requester and description voice information of the requester on the self condition; identifying the image information of the requester, and extracting the historical physical examination information of the requester stored in a management platform database; updating corresponding data of the historical physical examination information based on the obtained current information to obtain current data information; the current information is body data information of the requester provided by the wearable terminal device; processing the descriptive voice information of the requester to obtain key semantics; generating a requester data table based on the current data information and the key semantics; processing the requester data table to obtain abnormal data of the requester; and recommending physical examination packages to the requester based on the anomaly data of the requester.

Optionally, the identifying the image information of the requester, extracting the historical physical examination information of the requester stored in a management platform database, includes: extracting and storing the image frames of the request video into a picture format to generate image information of the requester; determining an identification area of the requester from the image information of the requester; extracting features of the identification area of the requester by using a neural network to obtain a facial image of the requester; matching the facial image of the requester with the facial image of the user stored in the management platform database to obtain a matching result; and extracting historical physical examination information of the requester based on the matching result.

Optionally, the processing the descriptive voice information of the requester to obtain key semantics includes: extracting descriptive voice information in the request video and storing the descriptive voice information as an audio file; preprocessing the audio file to obtain a target audio file; extracting features of the target audio file by using a neural network to generate an editable text; feeding back the editable text to the client application program so that the client application program displays and/or plays the editable text; and acquiring the collating and editing information of the requester on the editable text to obtain the key semantics.

Optionally, the processing the requester data table to obtain the exception data of the requester includes: preprocessing the current data information of the requester to obtain target data information; performing feature recognition on the target data information to obtain various body indexes of the requester; and comparing various corresponding physical indexes of the requester based on preset parameter thresholds to obtain abnormal data of the requester.

Optionally, recommending a physical examination package to the requester based on the anomaly data of the requester includes: the physical examination package is sent to a first user side application program which uploads the request video, so that a user interface of the first user side application program displays the physical examination package for the requester; and/or sending the physical examination package to the first user side application program and a second user side application program associated with the first user side application program, so that a user interface of the first user side application program displays the physical examination package for the requester and a user interface of the second user side application program displays the physical examination package for an associated person of the requester.

Optionally, after recommending a physical examination package to the requester based on the anomaly data of the requester, the method further comprises: acquiring user feedback information sent by the user side application program; if the user feedback information is adopted, acquiring a physical examination report of the requester, and archiving the physical examination report to the historical physical examination information of the requester; if the user feedback information is "unadopted", recommending a physical examination mechanism to the requester based on preset conditions.

Optionally, the recommending the physical examination mechanism to the requester based on the preset condition includes: scoring the physical examination mechanism in the registration catalog based on the physical examination package, and determining the physical examination mechanism equal to a first threshold as a first target physical examination mechanism; scoring the first target physical examination mechanism based on a pre-established user scoring rule, and determining the first target physical examination mechanism higher than a second preset threshold value as a second target physical examination mechanism; scoring the second target physical examination mechanism based on address information preset by the requester, and determining the second target physical examination mechanism smaller than a third preset threshold value as a third target physical examination mechanism; recommending the third target physical examination organization to the requester.

Optionally, the method further comprises: identifying current information of the requester; and prompting the requester to go to a hospital for examination if the current information of the requester is greater than the corresponding second parameter threshold.

In addition, in order to achieve the above object, the present application also provides a human body index anomaly data processing system based on artificial intelligence, the system comprising: the system comprises a user side application program, a user side application program and a user side application program, wherein the user side application program is carried on a mobile terminal of a requester, and is used for shooting a request video in a monitoring mode, and the request video comprises image information of the requester and description voice information of the requester on the condition of the user side application program; the data processing platform is in communication connection with the user side application program; the data processing platform is used for acquiring a request video shot by the user application program in a monitoring mode; identifying the image information of the requester in the request video, and extracting the historical physical examination information of the requester stored in a management platform database; updating corresponding data of the historical physical examination information based on the obtained current information to obtain current data information; the current information is body data information of the requester provided by the wearable terminal device; processing the description voice information of the requester in the request video to obtain key semantics; generating a requester data table based on the current data information and the key semantics; processing the requester data table to obtain abnormal data of the requester; and recommending physical examination packages to the requester based on the anomaly data of the requester.

Optionally, the client application program includes a first client application program and a second client application program, where the first client application program is associated with the first client application program, and the first client application program is configured to capture the request video and send the request video to the management platform in a monitoring mode, receive a physical examination package sent by the management platform, send acquired user feedback information to the management platform, and/or receive a physical examination mechanism recommended by the management platform; the second user side application program is used for receiving the physical examination package of the requester and/or receiving the physical examination mechanism recommended by the management platform, wherein the physical examination package is sent by the management platform.

In addition, in order to achieve the above object, the present application also provides a human body index anomaly data processing device based on artificial intelligence, the device comprising:

The video acquisition module is used for acquiring a request video shot by a user side application program in a monitoring mode, wherein the request video comprises image information of a requester and description voice information of the requester on the self condition;

the identification and extraction module is used for identifying the image information of the requester and extracting the historical physical examination information of the requester stored in the management platform database;

The data updating module is used for updating the corresponding data of the historical physical examination information based on the acquired current information to obtain current data information; the current information is body data information of the requester provided by the wearable terminal device;

the first processing module is used for processing the descriptive voice information of the requester to obtain key semantics;

the data generation module is used for generating a requester data table based on the current data information and the key semantics;

the second processing module is used for processing the requester data table to obtain the abnormal data of the requester;

And the recommendation sending module is used for recommending physical examination packages to the requester based on the abnormal data of the requester.

Furthermore, the present application provides a computing device, the computing device comprising: at least one processor, memory, and input output unit; wherein the memory is configured to store a computer program and the processor is configured to invoke the computer program stored in the memory to perform the method of any of the above.

Furthermore, the application provides a computer readable storage medium comprising instructions which, when run on a computer, cause the computer to perform the method of any of the above.

According to the human body index abnormal data processing method and system based on artificial intelligence, the historical physical examination information of a requester is obtained by identifying the image information of a request video; the current data information is obtained by updating the historical physical examination information; the key semantics are obtained by processing the description voice information of the request video; obtaining a requester data table through the current data information and the key semantics; obtaining abnormal data of the requester by processing the requester data table; recommending physical examination packages to the requester by obtaining abnormal data of the requester; therefore, when the requester cannot regularly go to the physical examination mechanism because of the replacement of the city or the residence due to work or other reasons, the health condition of the requester can be tracked without being limited by regions, physical examination mechanisms and time, the health requirement of the requester is met to a certain extent, and the flexibility and convenience of physical examination data management are improved.

Drawings

FIG. 1 is a schematic diagram of a human body index anomaly data processing system based on artificial intelligence according to an embodiment of the present application;

FIG. 2 is a flow chart of a method for processing abnormal human body index data based on artificial intelligence according to an embodiment of the present application;

FIG. 3 is a schematic diagram of a functional module of an apparatus for processing abnormal human body index data based on artificial intelligence according to an embodiment of the present application;

FIG. 4 is a schematic diagram of a medium according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of a computing device according to an embodiment of the present application.

The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.

Detailed Description

It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

Those skilled in the art will appreciate that embodiments of the application may be implemented as a system, apparatus, device, method, or computer program product. Thus, the application may be embodied in the form of: complete hardware, complete software (including firmware, resident software, micro-code, etc.), or a combination of hardware and software.

Physical examination refers to the performance of a series of examinations and tests on the body to assess the health of an individual and to find potential health problems. Therefore, it is important to maintain personal health to go to a hospital or a professional physical examination place for physical examination at regular intervals. However, existing physical examination modes often have some limitations. For example, people can usually go to a hospital or physical examination center where they live, which limits the flexibility and convenience of physical examination to some extent. This limitation is particularly evident for those who frequently change cities or habitable areas for work or other reasons. They may not be able to find a proper physical examination facility in a new city in time or miss an important physical examination because of time urgency. Furthermore, even if physical examination is performed, they may not be able to acquire own body abnormality data in time due to the deficiency of data management and tracking, thereby missing the best opportunity for early intervention and treatment.

The main solutions of the embodiments of the present application are: acquiring a request video shot by a user side application program in a monitoring mode, wherein the request video comprises image information of a requester and description voice information of the requester on the self condition; identifying the image information of the requester, and extracting the historical physical examination information of the requester stored in a management platform database; updating corresponding data of the historical physical examination information based on the obtained current information to obtain current data information; the current information is the body data information of the requester provided by the wearable terminal device; processing the descriptive voice information of the requester to obtain key semantics; generating a requester data table based on the current data information and the key semantics; processing the requester data table to obtain abnormal data of the requester; based on the anomaly data of the requester, a physical examination package is recommended to the requester.

The application provides a solution, which is to obtain the historical physical examination information of a requester by identifying the image information of a request video; the current data information is obtained by updating the historical physical examination information; the key semantics are obtained by processing the description voice information of the request video; obtaining a requester data table through the current data information and the key semantics; obtaining abnormal data of the requester by processing the requester data table; recommending physical examination packages to the requester by obtaining abnormal data of the requester; therefore, when the requester cannot regularly go to the physical examination mechanism because of the replacement of the city or the residence due to work or other reasons, the health condition of the requester can be tracked without being limited by regions, physical examination mechanisms and time, the health requirement of the requester is met to a certain extent, and the flexibility and convenience of physical examination data management are improved.

It should be noted that any number of elements in the figures are for illustration and not limitation, and that any naming is used for distinction only and not for limitation.

The principles of the present application are explained in detail below with reference to several representative embodiments thereof.

Referring to fig. 1, a schematic structural diagram of a human index anomaly data processing system based on artificial intelligence is provided in an embodiment of the present application. The human body index abnormal data processing system based on artificial intelligence comprises a user side application program and a data processing platform 120, wherein the data processing platform 120 is in communication connection with the user side application program.

The client application program is loaded on the mobile terminal 110 of the requester, and the client application program shoots a request video in a monitoring mode and sends the request video to the data processing platform 120, wherein the request video comprises image information of the requester and description voice information of the requester on the self condition.

The data processing platform 120 acquires a request video shot by a user side application program in a monitoring mode; identifying the image information of the requester in the request video, and extracting the historical physical examination information of the requester; updating corresponding data of the historical physical examination information based on the obtained current information to obtain current data information; the current information is the body data information of the requester provided by the wearable terminal device; processing the description voice information of the requester in the request video to obtain key semantics; generating a requester data table based on the current data information and the key semantics; processing the requester data table to obtain abnormal data of the requester; based on the anomaly data of the requester, a physical examination package is recommended to the requester.

As can be understood from fig. 2, the client application is installed on the mobile terminal 110 of the requester, and when the requester cannot regularly go to a fixed physical examination facility because of a change of city or residence for work or other reasons, the requester can shoot a request video in a monitoring mode of the client application, and the physical condition of the requester can be described in detail in the request video; the data processing platform 120 processes the shooting request video uploaded by the user side application program of the requester to finally obtain the abnormal data of the requester, and recommends physical examination packages to the requester based on the abnormal data of the requester, so that the requester can track the health condition of the requester without being limited by regions, physical examination institutions and time, the health requirement of the requester is met to a certain extent, and the flexibility and convenience of physical examination data management are improved.

In some modes, the client application program comprises a first client application program and a second client application program, the first client application program is associated with the first client application program, and the first client application program is used for shooting a request video and sending the request video to the management platform, receiving a physical examination package sent by the management platform, sending acquired user feedback information to the management platform and/or receiving physical examination mechanisms recommended by the management platform in a monitoring mode; the second user side application program is used for receiving the physical examination package of the requester sent by the management platform and/or receiving the physical examination mechanism recommended by the management platform.

In other modes, the data processing platform can be provided with a plurality of user side interfaces, the plurality of user side interfaces can be correspondingly connected with the mobile terminals carrying the user side application programs, the mobile terminals carrying the user side application programs corresponding to one user side interface can be associated with a plurality of mobile terminals, the plurality of mobile terminals can respectively correspond to the associated persons of the requester, when the associated persons of the requester and the requester receive the physical examination set after meal, the associated person of the requester can accompany the requester when the requester cannot independently examine the mechanism.

It should be noted that, in the embodiment of the present application, the personal privacy, the historical physical examination information, the current information and the personal information of the associated person of the requester need to be acquired under the consent of the requester and the associated person of the requester, and have security responsibility on the above information, so that infringement is not caused to the privacy of the requester and the associated person of the requester.

In order to illustrate the structure of a human index abnormal data processing system based on artificial intelligence, fig. 1 illustrates a mobile terminal with a user application program by using a mobile phone, but the above description is not limited to the embodiment of the present application.

Referring to fig. 2, an embodiment of the present application provides a method for processing abnormal human body index data based on artificial intelligence, where the method is applied to the data processing platform 120, and the method includes:

Step S210, obtaining a request video shot by a user side application program in a monitoring mode.

In an example embodiment, the requested video is a video photographed in the monitoring mode by the mobile terminal 110 of the above-described embodiment. The request video includes image information of the requester and descriptive voice information of the requester on its own. The image information of the requester includes a background image and a face image of the requester. The descriptive voice information includes a description of the physical condition of the requester, such as serious hair loss, insomnia for two or three days, blurred vision, etc., for one week in succession.

When a requester cannot regularly go to a fixed physical examination mechanism due to city replacement or residence replacement or other reasons, a user side application program loaded on the mobile terminal is operated, the user side application program starts a camera of the mobile terminal to shoot the requester in a monitoring mode, packages videos after shooting is completed to obtain a request video, and sends the request video to a data processing platform.

It should be noted that, in this exemplary embodiment, the user side application program includes a normal mode and a monitoring mode, and in the normal mode, information such as health life suggestions and disease preventive measures is displayed on a user interface of the user side application program. In the monitoring mode, the user interface of the user side application program is a camera interface, and after shooting is completed, the user side application program automatically exits the monitoring mode and switches to the normal mode.

Through shooting the request video, the user can explain the situation without manual input, and the user operation is greatly simplified.

Step S220, the image information of the requester is identified, and the history physical examination information of the requester stored in the management platform database is extracted.

In an example embodiment, the historical physical examination information is a summary of physical examination records of the requestor at a registration physical examination institution of the data processing platform. The historical physical examination information may include the requestor's historical physical examination institution, physical examination department, physical examination time, examination reports, diagnostic results, medical costs, physical examination plans, other relevant information, and the like. Wherein, the physical examination time comprises the date and time of each physical examination; the examination report includes results of various medical examinations (such as X-ray, CT, MRI, ultrasonic, etc.) and laboratory examinations (such as blood routine, urine routine, biochemical examinations, etc.), as well as surgical records including the procedure, results, post-operative notes, etc.; the diagnosis results comprise diagnosis comments of doctors, medication catalogues and the like; the physical examination plan includes a regular physical examination plan that a doctor would make for a physical examination user, such as how long the doctor is going to a physical examination facility for physical examination, and the like. Other relevant information such as allergy history, family medical history, etc.

In a specific embodiment, the step S220 may include: extracting and storing the image frames of the request video as a picture format to generate image information of a requester; determining an identification area of the requester from the image information of the requester; extracting features of the identification area of the requester by using a neural network to obtain a facial image of the requester; matching the facial image of the requester with the facial image of the physical examination user stored in the management platform database to obtain a matching result; based on the matching result, historical physical examination information of the requester is extracted.

As can be appreciated, each frame of image in the requested video is extracted using OCR (Optical Character Recognition ) techniques and saved as a picture format, such as JPG or PNG; then, preprocessing each frame of image information, such as performing geometric adjustment, color correction and the like on the image information, then, identifying the preprocessed image obtained after preprocessing, specifically, selecting an identification area of the preprocessed image by using a selection frame of a neural network, mainly intercepting a head image with a requester to generate a target image, and then, performing feature extraction on the intercepted target image by using the neural network to obtain a face image of the requester; and then, comparing the facial image of the requester with the facial image of the physical examination user stored in the management platform database by using the neural network, and determining the identity of the requester. If the facial image of the requester is successfully matched with the facial image of the physical examination user stored in the management platform database, proving that the requester is detected by a physical examination mechanism registered in the data processing platform, and at the moment, retrieving the historical physical examination information of the requester; if the facial image of the requester is not successfully matched with the facial image of the physical examination user stored in the management platform database, the fact that the physical examination mechanism registered by the requester on the data processing platform is not checked is proved, and at the moment, the requester is recommended to go to the physical examination mechanism registered by the data processing platform for physical examination, so that the history physical examination information can be conveniently established later.

Step S230, updating corresponding data of the historical physical examination information based on the obtained current information to obtain current data information.

In an example embodiment, the current information is requester's body data information provided by the wearable terminal device. Wearable terminal devices such as blood pressure meters, blood glucose meters, thermometers, body weights, stethoscopes, home pulse oximeters, and other intelligent devices capable of measuring the above data.

The history physical examination information of the requester is updated through the acquired current information, so that the current physical condition of the requester is more accurate, and the accuracy of recommending physical examination packages can be effectively improved.

Step S240, the descriptive voice information of the requester is processed to obtain key semantics.

In connection with the above example embodiments, key semantics are for example: "stay up" and "insomnia", "alopecia" and "blurred vision" etc.

In a specific embodiment, the step S240 may include: extracting descriptive voice information in the request video and storing the descriptive voice information as an audio file; preprocessing an audio file to obtain a target audio file; extracting features of the target audio file by using a neural network to generate an editable text; feeding back the editable text to the user side application program so that the user side application program can display and/or play the editable text; and acquiring the collating and editing information of the editable text by the requester to obtain key semantics.

It will be appreciated that audio processing software is used to extract the voice information in the requested video and store it in an audio format such as MP3 or WAV. And then preprocessing the audio file to obtain a target audio file, for example, performing operations such as noise reduction, standardization (such as normalization), framing and the like on the audio file. Then, the neural network is utilized to extract the characteristics of the target audio file, such as removing the word of the speech-removing aid, forming the key semantic of the audio file, generating the editable text based on the key semantic of the audio file, then feeding back the editable text to the user side application program, the user side application program displays and plays the editable text, so that the requester can conveniently collate and edit the editable text to confirm that the abnormal physical state of the editable text described in the editable text is accurate, and then the user side application program obtains the collating and editing information of the requester to obtain key semantics.

It should be noted that the neural network involved in the above steps S220 and S240 is a deep learning model, such as a Convolutional Neural Network (CNN) model. And if the requester cannot clearly and accurately express the self-situation because of personal factors such as dialect, the data processing platform cannot accurately extract the key semantics, and at this time, the data retrieval and learning capability of AIGC (ARTIFICIAL INTELLIGENCE GENERATED Content) artificial intelligence technology can be adopted to refer to the historical physical examination information of the requester to obtain the key semantics.

Step S250, a requester data table is generated based on the current data information and the key semantics.

Step S260, the requester data table is processed to obtain the exception data of the requester.

In a specific embodiment, the step S260 may include: preprocessing the current data information of the requester to obtain target data information; performing feature recognition on the target data information to obtain various physical indexes of the requester; and comparing various body indexes of the corresponding requester based on various preset parameter thresholds to obtain abnormal data of the requester.

As can be appreciated in connection with the above embodiments, for example, the historical physical examination information is cleaned, formatted, deleted and standardized to obtain the target information; the target information may include: inspection report of the requester, etc.; performing feature recognition on the inspection report in the target data information to obtain various physical indexes of the requester; for example, obtaining a heart rate value and a blood pressure value of the requester; the preset parameter thresholds comprise a heart rate normal range value and a blood pressure normal range value, the heart rate of the requester is compared with the heart rate range value and the blood pressure normal range value, the heart rate of the requester is obtained to exceed the heart rate normal range value, and the heart rate of the requester is abnormal data.

It should be noted that, the above parameter thresholds may be set according to different physical conditions of the requester, or may be set by a background program developer according to common medical knowledge, and the present exemplary embodiment is not limited specifically.

By obtaining the abnormal data of the requester, the accuracy of recommending the physical examination package can be improved, so that the recommended physical examination package is more in line with the current physical condition of the requester, and the requester is further convenient to monitor the health of the requester.

Step S270, recommending a physical examination package to the requester based on the abnormality data of the requester.

In an example embodiment, sending the physical examination package to the client application may include sending the physical examination package to the client application that uploads the requested video, sending the physical examination package to other client applications associated with the client application that uploads the requested video, and sending the physical examination package to other client applications associated with the client application that uploads the requested video simultaneously.

In a specific embodiment, the step S270 may include: and sending the physical examination package to the first client application program which uploads the request video, so that the physical examination package is displayed to the requester by the user interface of the first client application program.

In another specific embodiment, the step S270 may include: and sending the physical examination packages to the first user side application program and a second user side application program associated with the first user side application program, so that the user interface of the first user side application program displays the physical examination packages for the requester and the user interface of the second user side application program displays the physical examination packages for the associated person of the requester.

By sending the physical examination packages to the correspondents of the requester, the correspondents of the requester can accompany the requester to go to the physical examination mechanism when the requester cannot independently go to the physical examination mechanism.

Step S210 to step S70 are implemented, and the historical physical examination information of the requester is obtained by identifying the image information of the request video; the current data information is obtained by updating the historical physical examination information; the key semantics are obtained by processing the description voice information of the request video; obtaining a requester data table through the current data information and the key semantics; obtaining abnormal data of the requester by processing the requester data table; recommending physical examination packages to the requester by obtaining abnormal data of the requester; therefore, when the requester cannot regularly go to the fixed physical examination mechanism because of the replacement of the city or residence due to work or other reasons, the health condition of the requester can be tracked without being limited by regions, physical examination mechanisms and time, the health requirement of the requester is met to a certain extent, and the flexibility and convenience of physical examination data management are improved.

In another embodiment of the present application, after the step S270, the method further includes: acquiring user feedback information sent by a user side application program; if the user feedback information is "adopted", acquiring a physical examination report of the requester, and archiving the physical examination report to the historical physical examination information of the requester; if the user feedback information is "unadopted", recommending the physical examination mechanism to the requester based on preset conditions.

In an example embodiment, the physical examination facility includes a hospital as well as a professional physical examination site.

It can be appreciated that, for example, the physical examination package is sent to the client application program in the data processing platform, the client application program prompts the requester whether to adopt the physical examination package, if the requester clicks the "adopted" button of the user interface of the client application program, the physical examination report of the requester is obtained, and the physical examination report can be uploaded by the physical examination organization of the requester or uploaded by the requester; if the requester clicks the "unadopted" button of the user interface of the client application, a physical examination mechanism is recommended to the requester based on preset conditions.

By acquiring feedback information of the requester, the physical examination organization can be recommended to the requester under the condition that the requester does not adopt the recommended physical examination package. Therefore, the requester can find a proper physical examination mechanism to carry out physical examination under the condition that the requester cannot find the proper physical examination mechanism in a new city in time or misses important physical examination due to time urgency, and the health requirement of the requester is further met.

Further, recommending the physical examination institution to the requester based on the preset condition may include: scoring the physical examination institutions in the registration catalog based on the physical examination packages, and determining the physical examination institutions equal to a first threshold as first target physical examination institutions; scoring the first target physical examination mechanism based on a pre-established user scoring rule, and determining the first target physical examination mechanism higher than a second preset threshold value as a second target physical examination mechanism; scoring the second target physical examination mechanism based on address information preset by the requester, and determining the second target physical examination mechanism smaller than a third preset threshold value as a third target physical examination mechanism; and recommending a third target physical examination organization to the requester.

It can be appreciated that the data management platform records a list of registered physical examination institutions, lists physical examination items under each list of physical examination institutions, scores the registered physical examination institutions according to the items in the recommended physical examination packages, wherein the physical examination institutions including all physical examination items in the physical examination packages can be 10 points, then selects physical examination institutions with user scores greater than a second preset threshold value from the physical examination institutions with all physical examination packages, then selects physical examination institutions with user scores greater than the second preset threshold value from the physical examination institutions with user scores less than a third preset threshold value from the physical examination institutions with user scores greater than the second preset threshold value, and finally recommends physical examination institutions with distances smaller than the third preset threshold value to the requesters.

It should be noted that, the second preset threshold and the third preset threshold are set by the requester according to the actual situation of the requester, which is not limited in this exemplary embodiment.

Through scoring many times physical examination mechanism, can improve the accuracy of recommending physical examination mechanism to the requester, make things convenient for the requester to go to physical examination mechanism and acquire good experience.

In another embodiment of the present application, after the step S250, the method further includes: identifying the current information of the requester; if the current information of the requester is greater than the corresponding second parameter threshold value, prompting the requester to go to the hospital for examination.

It will be appreciated that, for example, the data processing platform may identify the current information of the requester, and obtain a heart rate of the requester exceeding 150 beats/min or falling below 50 beats/min, and that abnormal heart rate may cause sudden cardiac arrest or heart failure of the requester, at which point the data processing platform may prompt the requester to go to a hospital for examination. In special cases, for example, in the case that the requester authorizes to make emergency calls, the data processing platform selects a hospital closest to the requester to make emergency calls according to the current position information of the requester, so that the life safety of the requester is ensured.

Having described the method of the exemplary embodiment of the present application, next, an artificial intelligence based human index anomaly data processing apparatus 300 of the exemplary embodiment of the present application will be described with reference to fig. 3, the artificial intelligence based human index anomaly data processing apparatus 300 comprising: a video acquisition module 310, an identification extraction module 320, a data update module 330, a first processing module 340, a data generation module 350, a second processing module 360, a recommendation transmission module 370; wherein,

The video acquisition module 310 is configured to acquire a request video captured by the client application program in the monitoring mode, where the request video includes image information of a requester and description voice information of the requester on the self situation;

The identification extraction module 320 is configured to identify image information of a requester, and extract historical physical examination information of the requester stored in the management platform database;

the data updating module 330 is configured to update corresponding data of the historical physical examination information based on the obtained current information, so as to obtain current data information; the current information is the body data information of the requester provided by the wearable terminal device;

The first processing module 340 is configured to process the descriptive voice information of the requester to obtain key semantics;

the data generation module 350 is configured to generate a requester data table based on the current data information and the key semantics;

the second processing module 360 is configured to process the requester data table to obtain exception data of the requester;

the recommendation sending module 370 is configured to recommend physical examination packages to the requester based on the exception data of the requester.

As an optional implementation manner, the identification extraction module 320 is further configured to extract and store an image frame of the requested video as a picture format to generate image information of the requester; determining an identification area of the requester from the image information of the requester; extracting features of the identification area of the requester by using a neural network to obtain a facial image of the requester; matching the facial image of the requester with the facial image of the physical examination user stored in the management platform database to obtain a matching result; based on the matching result, historical physical examination information of the requester is extracted.

As an optional implementation manner, the first processing module 340 is further configured to extract the descriptive voice information in the requested video and store the descriptive voice information as an audio file; preprocessing an audio file to obtain a target audio file; extracting features of the target audio file by using a neural network to generate an editable text; feeding back the editable text to the user side application program so that the user side application program can display and/or play the editable text; and acquiring the collating and editing information of the editable text by the requester to obtain key semantics.

As an optional implementation manner, the data generating module 350 is further configured to pre-process the current data information of the requester to obtain the target data information; performing feature recognition on the target data information to obtain various physical indexes of the requester; and comparing various body indexes of the corresponding requester based on various preset parameter thresholds to obtain abnormal data of the requester.

As an optional implementation manner, the recommendation sending module 370 is further configured to send a physical examination package to the first client application program that uploads the requested video, so that the user interface of the first client application program displays the physical examination package to the requester; and/or sending the physical examination packages to the first user side application program and the second user side application program associated with the first user side application program, so that the user interface of the first user side application program displays the physical examination packages for the requester and the user interface of the second user side application program displays the physical examination packages for the associated person of the requester.

As an optional implementation manner, the human body index abnormal data processing device 300 based on artificial intelligence is further configured to obtain user feedback information sent by a user application program; if the user feedback information is "adopted", acquiring a physical examination report of the requester, and archiving the physical examination report to the historical physical examination information of the requester; if the user feedback information is "unadopted", recommending the physical examination mechanism to the requester based on preset conditions.

As an optional implementation manner, the human body index abnormal data processing apparatus 300 based on artificial intelligence is further configured to score the physical examination mechanism in the registration catalog based on the physical examination package, and determine the physical examination mechanism equal to the first threshold as the first target physical examination mechanism; scoring the first target physical examination mechanism based on a pre-established user scoring rule, and determining the first target physical examination mechanism higher than a second preset threshold value as a second target physical examination mechanism; scoring the second target physical examination mechanism based on address information preset by the requester, and determining the second target physical examination mechanism smaller than a third preset threshold value as a third target physical examination mechanism; and recommending a third target physical examination organization to the requester.

As an optional implementation manner, the human body index anomaly data processing device 300 based on artificial intelligence is further used for identifying the current information of the requester; if the current information of the requester is greater than the corresponding second parameter threshold value, prompting the requester to go to the hospital for examination.

It should be noted that, the beneficial effects of the human body index abnormal data processing apparatus 300 based on artificial intelligence are the same as the beneficial effects of the human body index abnormal data processing method based on artificial intelligence, and are not described in detail in this embodiment.

Having described the method and apparatus of the exemplary embodiment of the present application, reference is next made to fig. 4 for describing a computer readable storage medium of the exemplary embodiment of the present application, and referring to fig. 4, the computer readable storage medium is shown as an optical disc 40, on which a computer program (i.e., a program product) is stored, where the computer program, when executed by a processor, implements the steps described in the foregoing method embodiment, for example, obtaining a request video captured by a client application program in a monitoring mode, where the request video includes image information of a requester and descriptive voice information of the requester about itself; identifying the image information of the requester, and extracting the historical physical examination information of the requester stored in a management platform database; updating corresponding data of the historical physical examination information based on the obtained current information to obtain current data information; the current information is the body data information of the requester provided by the wearable terminal device; processing the descriptive voice information of the requester to obtain key semantics; generating a requester data table based on the current data information and the key semantics; processing the requester data table to obtain abnormal data of the requester; recommending physical examination packages to the requester based on the exception data of the requester; the specific implementation of each step is not repeated here.

It should be noted that examples of the computer readable storage medium may also include, but are not limited to, a phase change memory (PRAM), a Static Random Access Memory (SRAM), a Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a flash memory, or other optical or magnetic storage medium, which will not be described in detail herein.

Having described the methods, apparatus and media of exemplary embodiments of the present application, next, a computing device for model processing of exemplary embodiments of the present application is described with reference to FIG. 5.

FIG. 5 illustrates a block diagram of an exemplary computing device 50 suitable for use in implementing embodiments of the application, the computing device 50 may be a computer system or a server. The computing device 50 shown in fig. 5 is merely an example and should not be taken as limiting the functionality and scope of use of embodiments of the present application.

As shown in fig. 5, components of computing device 50 may include, but are not limited to: one or more processors or processing units 501, a system memory 502, and a bus 503 that connects the various system components (including the system memory 502 and processing units 501).

Computing device 50 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by computing device 50 and includes both volatile and nonvolatile media, removable and non-removable media.

The system memory 502 may include computer system readable media in the form of volatile memory, such as RAM 5021, which is random access memory, and/or cache memory 5022. Computing device 50 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, ROM 5023 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5 and commonly referred to as a "hard drive"). Although not shown in fig. 5, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media), may be provided. In such cases, each drive may be coupled to bus 503 through one or more data medium interfaces. The system memory 502 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of embodiments of the application.

A program/utility 5025 having a set (at least one) of program modules 5024 may be stored in, for example, system memory 502, and such program modules 5024 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 5024 generally perform the functions and/or methods of the described embodiments of the present application.

Computing device 50 may also communicate with one or more external devices 504 (e.g., keyboard, pointing device, display, etc.). Such communication may occur through an I/O interface 505, which is an input/output interface. Moreover, computing device 50 may also communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through network adapter 506. As shown in fig. 5, network adapter 506 communicates with other modules of computing device 50, such as processing unit 501, etc., via bus 503. It should be appreciated that although not shown in fig. 5, other hardware and/or software modules may be used in connection with computing device 50.

The processing unit 501 executes various functional applications and data processing by running a program stored in the system memory 502, for example, acquires a request video shot by a user side application program in a monitoring mode, the request video including image information of a requester and descriptive voice information of the requester on own; identifying the image information of the requester, and extracting the historical physical examination information of the requester stored in a management platform database; updating corresponding data of the historical physical examination information based on the obtained current information to obtain current data information; the current information is the body data information of the requester provided by the wearable terminal device; processing the descriptive voice information of the requester to obtain key semantics; generating a requester data table based on the current data information and the key semantics; processing the requester data table to obtain abnormal data of the requester; based on the anomaly data of the requester, a physical examination package is recommended to the requester. The specific implementation of each step is not repeated here. It should be noted that while several units/modules or sub-units/sub-modules of an artificial intelligence based human metric exception data processing device are mentioned in the above detailed description, such a division is merely exemplary and not mandatory. Indeed, the features and functionality of two or more units/modules described above may be embodied in one unit/module in accordance with embodiments of the present application. Conversely, the features and functions of one unit/module described above may be further divided into ones that are embodied by a plurality of units/modules.

In the description of the present application, it should be noted that the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.

In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

Finally, it should be noted that: the above examples are only specific embodiments of the present application, and are not intended to limit the scope of the present application, but it should be understood by those skilled in the art that the present application is not limited thereto, and that the present application is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Furthermore, although the operations of the methods of the present application are depicted in the drawings in a particular order, this is not required or suggested that these operations must be performed in this particular order or that all of the illustrated operations must be performed in order to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform.

Claims

1. The human body index abnormal data processing method based on artificial intelligence is characterized by comprising the following steps of:

Acquiring a request video shot by a user side application program in a monitoring mode, wherein the request video comprises image information of a requester and description voice information of the requester on the self condition;

identifying the image information of the requester, and extracting the historical physical examination information of the requester stored in a management platform database;

Updating corresponding data of the historical physical examination information based on the obtained current information to obtain current data information; the current information is body data information of the requester provided by the wearable terminal device;

Processing the descriptive voice information of the requester to obtain key semantics;

generating a requester data table based on the current data information and the key semantics;

Processing the requester data table to obtain abnormal data of the requester;

and recommending physical examination packages to the requester based on the anomaly data of the requester.

2. The method of claim 1, wherein the identifying the image information of the requester, extracting historical physical examination information of the requester stored in a management platform database, comprises:

extracting and storing the image frames of the request video into a picture format to generate image information of the requester;

Determining an identification area of the requester from the image information of the requester;

Extracting features of the identification area of the requester by using a neural network to obtain a facial image of the requester;

matching the facial image of the requester with the facial image of the user stored in the management platform database to obtain a matching result;

And extracting historical physical examination information of the requester based on the matching result.

3. The method of claim 1, wherein processing the descriptive voice information of the requestor to obtain key semantics comprises:

extracting descriptive voice information in the request video and storing the descriptive voice information as an audio file;

Preprocessing the audio file to obtain a target audio file;

extracting features of the target audio file by using a neural network to generate an editable text;

feeding back the editable text to the client application program so that the client application program displays and/or plays the editable text;

And acquiring the collating and editing information of the requester on the editable text to obtain the key semantics.

4. The method of claim 1, wherein processing the requester data table to obtain the exception data for the requester comprises:

Preprocessing the current data information of the requester to obtain target data information;

Performing feature recognition on the target data information to obtain various body indexes of the requester;

And comparing various corresponding physical indexes of the requester based on preset parameter thresholds to obtain abnormal data of the requester.

5. The method of claim 1, wherein recommending a physical examination package to the requestor based on the requestor's exception data comprises:

The physical examination package is sent to a first user side application program which uploads the request video, so that a user interface of the first user side application program displays the physical examination package for the requester; and/or the number of the groups of groups,

And sending the physical examination package to the first user side application program and a second user side application program associated with the first user side application program, so that the user interface of the first user side application program displays the physical examination package for the requester and the user interface of the second user side application program displays the physical examination package for the associated person of the requester.

6. The method of any of claims 1-5, wherein after recommending a physical package to the requestor based on the exception data of the requestor, the method further comprises:

acquiring user feedback information sent by the user side application program;

if the user feedback information is adopted, acquiring a physical examination report of the requester, and archiving the physical examination report to the historical physical examination information of the requester;

If the user feedback information is "unadopted", recommending a physical examination mechanism to the requester based on preset conditions.

7. The method of claim 6, wherein recommending a physical examination facility to the requestor based on the preset condition comprises:

scoring the physical examination mechanism in the registration catalog based on the physical examination package, and determining the physical examination mechanism equal to a first threshold as a first target physical examination mechanism;

scoring the first target physical examination mechanism based on a pre-established user scoring rule, and determining the first target physical examination mechanism higher than a second preset threshold value as a second target physical examination mechanism;

Scoring the second target physical examination mechanism based on address information preset by the requester, and determining the second target physical examination mechanism smaller than a third preset threshold value as a third target physical examination mechanism;

Recommending the third target physical examination organization to the requester.

8. The method according to claim 1, wherein the method further comprises:

identifying current information of the requester;

and prompting the requester to go to a hospital for examination if the current information of the requester is greater than the corresponding second parameter threshold.

9. An artificial intelligence based human index anomaly data processing system, the system comprising:

The system comprises a user side application program, a user side application program and a user side application program, wherein the user side application program is carried on a mobile terminal of a requester, and is used for shooting a request video in a monitoring mode, and the request video comprises image information of the requester and description voice information of the requester on the condition of the user side application program;

The data processing platform is in communication connection with the user side application program; the data processing platform is used for acquiring a request video shot by the user application program in a monitoring mode; identifying the image information of the requester in the request video, and extracting the historical physical examination information of the requester stored in a management platform database; updating corresponding data of the historical physical examination information based on the obtained current information to obtain current data information; the current information is body data information of the requester provided by the wearable terminal device; processing the description voice information of the requester in the request video to obtain key semantics; generating a requester data table based on the current data information and the key semantics; processing the requester data table to obtain abnormal data of the requester; and recommending physical examination packages to the requester based on the anomaly data of the requester.

10. The system of claim 9, wherein the client application program comprises a first client application program and a second client application program, the first client application program is associated with the first client application program, and the first client application program is configured to capture the request video and send the request video to the management platform in a monitoring mode, receive a physical examination package sent by the management platform, send acquired user feedback information to the management platform, and/or receive a physical examination mechanism recommended by the management platform;

the second user side application program is used for receiving the physical examination package of the requester and/or receiving the physical examination mechanism recommended by the management platform, wherein the physical examination package is sent by the management platform.