CN115019924A - Health data acquisition and analysis method applying artificial intelligence health robot - Google Patents
Health data acquisition and analysis method applying artificial intelligence health robot Download PDFInfo
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Abstract
The invention provides a health data acquisition and analysis method applying an artificial intelligence health robot, which comprises the following steps: acquiring health data of residents in an area based on an artificial intelligence health robot; responding to an uploading instruction of the artificial intelligent health robot, uploading the health data of residents in the area to a preset health data cloud management platform, calling the health data of the residents in the area, acquired by the artificial intelligent health robot, loading the health data of the residents in the area into a cloud sharing database, analyzing the acquired health data of the residents in the area based on a pre-trained health data analysis model, generating a personalized analysis report, and outputting an analysis result. According to the embodiment of the invention, the health data of the residents in the region is analyzed and processed through the pre-trained health data analysis model, the personalized analysis report is customized for the residents in the region, and meanwhile, the medical care personnel can be assisted to rescue the patients, so that the data sharing is realized, and the success rate and the efficiency of treatment are improved.
Description
Technical Field
The invention relates to the technical field of medical treatment, in particular to the technical field of medical data analysis, and specifically relates to a health data acquisition and analysis method applying an artificial intelligent health robot.
Background
The burden of chronic diseases accounts for 70% of the total burden of diseases, and from the development of the chronic diseases in developed countries, the incidence of chronic diseases mainly including hypertension and diabetes will continuously rise in the next decades, although China invests a lot of resources in the prevention and control of chronic diseases, the prevention and control effect is not ideal, and the incidence and mortality of chronic diseases cannot be effectively reduced, so in order to prevent chronic diseases, health data collection and analysis are required to be regularly carried out on the primary group, but when people have medical health service demands, the medical health institutions are generally medical health institutions which are independently selected to provide services, for common people, due to lack of medical related knowledge, the health conditions and the urgency degree of the people cannot be effectively estimated, and in the face of medical health institutions with a large number of levels, the symptoms cannot be effectively selected, and great burden is brought to the work of preventing and treating chronic diseases.
Along with the continuous change of artificial intelligence technology, the extensive public health that is applied to basic level of artificial intelligence technology, can realize through artificial intelligence the collection to resident health data in the region, supplementary medical staff analysis and transmission health data, but current artificial intelligence assists the collection system and can't carry out whole automatic quantification's statistics and analysis to the service index, need rely on medical staff to judge and analyze the data of gathering, not only inefficiency, make mistakes very easily moreover, and then influence patient's treatment.
Therefore, in order to solve the problems, it is necessary to provide a better health data collecting and analyzing method to improve the accuracy and efficiency of health data collecting and analyzing.
Disclosure of Invention
In view of the above, the present invention provides an improved method for acquiring and analyzing health data by using an artificial intelligence health robot, so as to improve the accuracy and efficiency of data acquisition and analysis.
In view of the above objects, in one aspect, the present invention provides a health data collecting and analyzing method using an artificial intelligence health robot, wherein the method comprises the steps of:
acquiring resident health data in an area based on an artificial intelligence health robot, wherein the resident health data in the area comprises resident basic information and resident physical examination information corresponding to the resident basic information;
responding to an uploading instruction of the artificial intelligent health robot, uploading the health data of residents in the area to a preset health data cloud management platform, calling the health data of the residents in the area acquired by the artificial intelligent health robot by the health data cloud management platform, and loading the health data of the residents in the area into a cloud sharing database;
and loading the health data of residents in the area, traversing the cloud sharing database, analyzing the acquired health data of the residents in the area based on the pre-trained health data analysis model, generating a personalized analysis report, and outputting an analysis result.
In some embodiments of the health data collecting and analyzing method using an artificial intelligence health robot according to the present invention, the method for acquiring health data of residents in an area based on the artificial intelligence health robot specifically includes:
acquiring an acquisition instruction;
verifying the acquisition instruction, and creating or logging in a resident health data account;
and responding to the acquisition instruction, and acquiring the health data of the residents by the artificial intelligent health robot.
In some embodiments of the health data collecting and analyzing method using an artificial intelligence health robot according to the present invention, the method for collecting health data of a resident by an artificial intelligence health robot specifically includes:
identifying resident basic information;
user sign acquisition is executed through a health acquisition unit;
the resident physical examination information is sent, and the resident physical examination information is uploaded to a health data cloud management platform;
and acquiring a personalized analysis report, displaying the personalized analysis report, and sending an abnormal early warning.
In some embodiments of the health data collecting and analyzing method using an artificial intelligence health robot according to the present invention, the artificial intelligence health robot is mounted on a front-end wisdom collection task group, the front-end wisdom collection task group including:
the movable digital physical examination vehicle takes a special vehicle as a carrier, integrates various intelligent physical examination devices, and can realize real-time acquisition, transmission and processing of data;
the public health examination workstation supports multi-region synchronous work and simultaneous detection of multiple persons;
family doctor wisdom terminal that can conveniently carry.
In some embodiments of the health data collecting and analyzing method using an artificial intelligence health robot according to the present invention, the health data cloud management platform includes:
the health data acquisition unit is used for responding to an uploading instruction of the artificial intelligent health robot and acquiring health data of residents in an area;
the health data processing unit loads the health data of residents in the area, and carries out noise reduction, resampling and classification processing on the health data of the residents in the area to form a classified health data set;
and the health data sending unit loads the classified health data set and sends the health data set to the cloud sharing database.
In some embodiments of the health data collecting and analyzing method using an artificial intelligence health robot according to the present invention, the method for denoising, resampling and classifying the health data of residents in the area further comprises:
loading the health data of residents in the area;
acquiring a classified evaluation item of resident health data in an area, and discretizing the classified evaluation item to obtain a discretized classified evaluation item;
respectively calculating the association degrees between the resident health data in the single group of areas and the multiple groups of classified evaluation items by adopting a grey association degree method to form an association degree queue;
and loading the association degree queue, judging whether the association degree of the resident health data in the area and the classification evaluation items exceeds a set threshold, and if so, loading the resident health data in the area into at least one group of corresponding classification evaluation items.
In some embodiments of the health data collecting and analyzing method using an artificial intelligence health robot according to the present invention, the cloud shared database establishing method specifically includes:
acquiring a cloud sharing database topological structure tree;
loading a health data set and classification evaluation items corresponding to the health data set, and inputting the health data set and the classification evaluation items corresponding to the health data set into a cloud sharing database topological structure tree;
and generating a rendered cloud sharing database.
In some embodiments of the method for collecting and analyzing health data using an artificial intelligence health robot according to the present invention, the method for analyzing the health data analysis model specifically includes:
loading a cloud sharing database;
calling a real-time health data set, and indexing a historical health data set based on a preset data index format, wherein the historical health data set comprises main associated health data and auxiliary associated health data;
clustering the main associated health data, the auxiliary associated health data and the real-time health data set, acquiring outliers in the health data according to a clustering result, judging the abnormal degree of the outliers, and determining the corresponding real-time health data.
In some embodiments of the method for collecting and analyzing health data using an artificial intelligence health robot according to the present invention, the method for analyzing a health data analysis model further includes:
loading corresponding real-time health data;
extracting real-time health data abnormal diagnosis records in a cloud sharing database, and acquiring medical diagnosis records corresponding to the abnormal diagnosis records;
determining the disease species to be analyzed, analyzing the disease species, and acquiring the hospitalizing information, the treatment information and the rehabilitation nursing information corresponding to the disease species.
In another aspect of the present invention, the method for generating a personalized analysis report specifically includes:
obtaining analysis results, wherein the analysis results comprise a conventional physical examination report, abnormal early warning, intelligent assessment and health guidance;
and pushing the analysis result, and pushing the analysis result to the front-end intelligent acquisition working group, the doctor end and the user end in real time based on the communication protocol.
The invention has at least the following beneficial technical effects: according to the embodiment of the invention, the health data of the residents in the region is analyzed and processed through the pre-trained health data analysis model, the personalized analysis report is customized for the residents in the region, and meanwhile, the medical care personnel can be assisted to rescue the patients, so that the data sharing is realized, and the success rate and the efficiency of treatment are improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other embodiments can be obtained by using the drawings without creative efforts.
In the figure:
FIG. 1 is a schematic diagram illustrating a flow of an implementation of a health data collection and analysis method using an artificial intelligence health robot according to the present invention;
FIG. 2 is a schematic block diagram illustrating an embodiment of a method for acquiring health data of residents in an area based on an artificial intelligence health robot;
FIG. 3 shows a schematic block diagram of an embodiment of a method for an artificial intelligence health robot to collect resident health data;
FIG. 4 shows a schematic block diagram of an embodiment of a health data cloud management platform;
FIG. 5 shows a schematic block diagram of an embodiment of a method of noise reduction, resampling and classification processing of resident health data within an area;
FIG. 6 shows a schematic block diagram of an embodiment of a cloud shared database establishment method;
FIG. 7 shows a schematic block diagram of an embodiment of an analysis method of a health data analysis model.
Fig. 8 shows a schematic block diagram of an embodiment of a method of generating a personalized analysis report according to the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the following embodiments of the present invention are described in further detail with reference to the accompanying drawings.
It should be noted that all expressions using "first" and "second" in the embodiments of the present invention are used for distinguishing two non-identical entities with the same name or different parameters, and it is understood that "first" and "second" are only used for convenience of expression and should not be construed as limiting the embodiments of the present invention. Furthermore, the terms "comprises" and "comprising," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements does not include all of the other steps or elements inherent in the list.
In short, the invention provides a health data acquisition and analysis mode applying an artificial intelligence health robot, and aims at solving the problems that the conventional artificial intelligence auxiliary acquisition system cannot carry out full-process automatic quantitative statistics and analysis on service indexes, and needs to rely on medical staff to judge and analyze the acquired data, so that the efficiency is low, errors are easy to occur, and the treatment of a patient is influenced.
For this reason, the basic flow of the test includes the following points: the method comprises the steps of acquiring health data of residents in an area based on an artificial intelligence health robot, responding to an uploading instruction of the artificial intelligence health robot, uploading the health data of the residents in the area to a preset health data cloud management platform 100, calling the health data of the residents in the area acquired by the artificial intelligence health robot by the health data cloud management platform 100, loading the health data of the residents in the area into a cloud sharing database, loading the health data of the residents in the area, traversing the cloud sharing database, analyzing the health data of the residents in the area acquired based on a pre-trained health data analysis model, generating a personalized analysis report, and outputting an analysis result.
According to the embodiment of the invention, the health data of the residents in the region is analyzed and processed through the pre-trained health data analysis model, the personalized analysis report is customized for the residents in the region, and meanwhile, the medical care personnel can be assisted to rescue the patients, so that the data sharing is realized, and the success rate and the efficiency of treatment are improved.
To this end, in a first aspect of the present invention, a health data collection and analysis method using an artificial intelligence health robot is provided. Fig. 1 shows a schematic block diagram of an embodiment of a health data collection and analysis method applying an artificial intelligence health robot according to the present invention. In the embodiment shown in fig. 1, the method comprises:
and step S10, acquiring the health data of residents in the area based on the artificial intelligence health robot, wherein the health data of the residents in the area comprises the basic information of the residents and the physical examination information of the residents corresponding to the basic information of the residents.
Step S20, responding to the artificial intelligence health robot uploading instruction, uploading the in-region resident health data to the preset health data cloud management platform 100, and the health data cloud management platform 100 calls the in-region resident health data acquired by the artificial intelligence health robot and loads the in-region resident health data into the cloud sharing database.
And step S30, loading the health data of residents in the area, traversing the cloud sharing database, analyzing the acquired health data of the residents in the area based on the pre-trained health data analysis model, generating a personalized analysis report, and outputting an analysis result.
Illustratively, the resident basic information includes names, ages, heights, sexes, weights, residence places, and working properties of residents in the corresponding areas, the resident physical examination information corresponding to the resident basic information includes but is not limited to blood fat, cholesterol, low density lipoprotein, high density lipoprotein, apolipoprotein information, the system is used for screening hyperlipidemia and blood glucose data, and for screening diabetes, electrocardiogram, electroencephalogram and lung imaging subject examination data, and it should be noted that the health data of residents in an area comprises resident basic information and resident physical examination information corresponding to the resident basic information, which comprehensively covers the common disease characterization information of the residents, and the known regions can be divided by administrative units, vector diagrams of different administrative regions can also be extracted, and the obtained vector diagrams are equally divided and cut, so that the rasterization processing of the administrative regions is realized.
According to the embodiment of the invention, the health data of the residents in the region is analyzed and processed through the pre-trained health data analysis model, the personalized analysis report is customized for the residents in the region, and meanwhile, the medical care personnel can be assisted to rescue the patients, so that the data sharing is realized, and the success rate and the efficiency of treatment are improved.
The embodiment of the invention also provides a method for acquiring the health data of residents in the area based on the artificial intelligence health robot. Fig. 2 shows a schematic block diagram of an embodiment of a method for acquiring health data of residents in an area based on an artificial intelligence health robot. In the embodiment shown in fig. 2, the method comprises:
and step S101, acquiring a collection instruction.
And S102, verifying the acquisition instruction, and creating or logging in the resident health data account.
And S103, responding to the acquisition instruction, and acquiring the health data of the residents by the artificial intelligence health robot.
In this embodiment, the artificial intelligence health robot acquires the collection instruction, and when the collection instruction is acquired, in order to ensure the safety of public data and avoid information leakage, all instructions including but not limited to the collection instruction are encrypted, and the encrypted value is sent and transmitted in real time together with the instruction and the information, and in this embodiment, the encryption algorithm includes but not limited to SM3 cryptographic algorithm and hash algorithm.
Meanwhile, it is pointed out that the artificial intelligence health robot is provided with a communication module, and the communication module acquires or sends an instruction through 5G communication or wifi communication.
Illustratively, the artificial intelligence health robot is carried on front-end wisdom collection workgroup, front-end wisdom collection workgroup includes:
the movable digital physical examination vehicle takes a special vehicle as a carrier, integrates various intelligent physical examination devices, and can realize real-time acquisition, transmission and processing of data;
the public health examination workstation supports multi-region synchronous work and simultaneous detection of multiple persons;
family doctor wisdom terminal that can conveniently carry.
It should be noted that the artificial intelligence health robot is specifically an AI health management robot, which integrates core functions of home doctor service, dynamic health monitoring, health archives, health guidance, health education and the like based on NLP and TTS as core technologies and on data of home doctor subscription, follow-up visit and public health physical examination, and adopts a one-touch aging modification. Not only can realize three-level linkage of expert doctors, family medical teams and resident families; meanwhile, based on strong data operation, memory, perception, learning, action and treatment capacity of the gradually-healthy and medical and mental healthy brain, the method collects multi-dimensional data of the old user in healthy physiological indexes, living behaviors and the like, carries out accurate identification, accurate positioning, accurate portrait and accurate service, and finally realizes safe and accessible dynamic management of public health service and closed loop of digital health management.
Meanwhile, the movable digital physical examination vehicle is provided with various detection auxiliary devices, so that the detection requirements of different disease types are met, and the detection auxiliary devices comprise, but are not limited to, an electrocardiograph, a weight and height scale, a B-type ultrasonic blood pressure meter, a full-automatic biochemical analyzer, a computerized urine machine, a television (health promotion and education), a central control touch screen, an A3 printer, a medical centrifuge, a microphone, a refrigerator, a blood ball machine and a camera.
The embodiment of the invention also provides a method for acquiring the resident health data by the artificial intelligent health robot. FIG. 3 shows a schematic block diagram of an embodiment of a method for an artificial intelligence health robot to collect resident health data. In an embodiment as shown in fig. 3, the method comprises:
in step S1031, the resident basic information is identified.
And step S1032, user sign acquisition is executed through the health acquisition unit.
Step S1033, sending the resident examination information, and uploading the resident examination information to the health data cloud management platform 100.
And S1034, acquiring a personalized analysis report, displaying the personalized analysis report and sending out an abnormal early warning.
In this embodiment, the identification resident basic information is identified and authenticated through an identity card reader, the identity card reader is in communication connection with a working Pad, and a health record can be established through the working Pad to manage the user, wherein the management work includes new user contract signing management, performance management, follow-up visit management, performance management and physical examination management.
The embodiment of the invention also provides a health data cloud management platform 100. Fig. 4 shows a schematic block diagram of an embodiment of a health data cloud management platform 100. In the embodiment shown in fig. 4, the health data cloud management platform 100 includes:
the health data acquisition unit 110 is used for responding to an artificial intelligent health robot uploading instruction and acquiring health data of residents in an area;
the health data processing unit 120 loads the health data of residents in the area, and performs noise reduction, resampling and classification on the health data of the residents in the area to form a classified health data set;
and the health data sending unit 130 loads the classified health data set and sends the health data set to the cloud shared database.
In the present embodiment, fig. 5 shows a schematic block diagram of an embodiment of a method of noise reduction, resampling, and classification processing for resident health data in an area. The method for denoising, resampling and classifying the health data of residents in the area further comprises the following steps:
in step S201, the health data of the residents in the area is loaded.
Step S202, acquiring the classified evaluation items of the resident health data in the area, and performing discretization processing on the classified evaluation items to obtain discretized classified evaluation items.
Step S203, respectively calculating the association degrees between the resident health data in the single group of areas and the multiple groups of classification evaluation items by adopting a gray association degree method to form an association degree queue.
And step S204, loading the association degree queue, judging whether the association degree of the resident health data in the area and the classification evaluation items exceeds a set threshold, and if so, loading the resident health data in the area into at least one group of corresponding classification evaluation items.
In the embodiment, the threshold is preset, and is set for evaluating the association degree between the health data of the residents in the area and the classification evaluation items.
The embodiment of the invention also provides a cloud sharing database establishing method. Fig. 6 shows a schematic block diagram of an embodiment of a cloud shared database establishment method. In an embodiment as shown in fig. 6, the method comprises:
step S301, a cloud sharing database topological structure tree is obtained.
Step S302, loading the health data set and the classification evaluation items corresponding to the health data set, and inputting the health data set and the classification evaluation items corresponding to the health data set into a cloud sharing database topological structure tree.
Step S303, a rendered cloud sharing database is generated.
In this embodiment, the classification evaluation item is used for classifying the health data set, so as to classify the disordered data, for example, the data may be classified based on disease types, or may be classified again in a cross manner, so as to produce the rendered cloud shared database, ensure the association degree between the data, and avoid the missing of the topology tree of the cloud shared database.
The embodiment of the invention also provides an analysis method of the health data analysis model. FIG. 7 shows a schematic block diagram of an embodiment of an analysis method of a health data analysis model. In an embodiment as shown in fig. 7, the method comprises:
step S401, loading a cloud sharing database.
Step S402, a real-time health data set is called, and a historical health data set is indexed based on a preset data index format, wherein the historical health data set comprises main associated health data and auxiliary associated health data.
Step S403, clustering the main associated health data, the auxiliary associated health data and the real-time health data set, acquiring outliers in the health data according to clustering results, judging the abnormal degree of the outliers, and determining the corresponding real-time health data.
Step S404, loading corresponding real-time health data.
Step S405, extracting real-time health data abnormal diagnosis records in the cloud sharing database, and acquiring medical diagnosis records corresponding to the abnormal diagnosis records.
Step S406, determining the disease species to be analyzed, analyzing the disease species, and acquiring the hospitalization information, the treatment information and the rehabilitation nursing information corresponding to the disease species.
In this embodiment, the health data analysis model is a convergent model, and the model modeling is based on a trained PointNet convolutional neural network model as a basic model.
The embodiment of the invention also provides a method for generating the personalized analysis report. Fig. 8 shows a schematic block diagram of an embodiment of a method of generating a personalized analysis report according to the invention. In an embodiment as shown in fig. 8, the method comprises:
step S501, obtaining analysis results, wherein the analysis results comprise a conventional physical examination report, abnormal early warning, intelligent evaluation and health guidance;
step S502, pushing the analysis result, and pushing the analysis result to the front-end intelligent acquisition workgroup, the doctor end and the user end in real time based on the communication protocol.
In this embodiment, after the analysis result is pushed, the intelligent collection workgroup, the doctor end and the user end need to query information after verification, and the verification manner includes, but is not limited to, a random character string, a fixed character string, voice recognition and facial feature recognition.
The medical end and the user end can be a notebook computer, a Personal Digital Assistant (PDA), a mobile phone, and other devices capable of communicating.
According to the embodiment of the invention, the health data of the residents in the region is analyzed and processed through the pre-trained health data analysis model, the personalized analysis report is customized for the residents in the region, and meanwhile, the medical care personnel can be assisted to rescue the patients, so that the data sharing is realized, and the success rate and the efficiency of treatment are improved.
The foregoing is an exemplary embodiment of the present disclosure, but it should be noted that various changes and modifications could be made herein without departing from the scope of the present disclosure as defined by the appended claims. The functions, steps and/or actions of the method claims in accordance with the disclosed embodiments described herein need not be performed in any particular order. Furthermore, although elements of the disclosed embodiments of the invention may be described or claimed in the singular, the plural is contemplated unless limitation to the singular is explicitly stated.
It should be understood that, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly supports the exception. It should also be understood that "and/or" as used herein is meant to include any and all possible combinations of one or more of the associated listed items. The numbers of the embodiments disclosed in the embodiments of the present invention are merely for description, and do not represent the merits of the embodiments.
Those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant only to be exemplary, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the idea of an embodiment of the invention, also technical features in the above embodiment or in different embodiments may be combined and there are many other variations of the different aspects of the embodiments of the invention as described above, which are not provided in detail for the sake of brevity. Therefore, any omissions, modifications, substitutions, improvements, and the like that may be made without departing from the spirit and principles of the embodiments of the present invention are intended to be included within the scope of the embodiments of the present invention.
Claims (10)
1. A health data acquisition and analysis method applying an artificial intelligence health robot is characterized by comprising the following steps:
acquiring resident health data in an area based on an artificial intelligence health robot, wherein the resident health data in the area comprises resident basic information and resident physical examination information corresponding to the resident basic information;
responding to an uploading instruction of the artificial intelligent health robot, uploading the health data of residents in the area to a preset health data cloud management platform, calling the health data of the residents in the area acquired by the artificial intelligent health robot by the health data cloud management platform, and loading the health data of the residents in the area into a cloud sharing database;
and loading the health data of residents in the area, traversing the cloud sharing database, analyzing the acquired health data of the residents in the area based on the pre-trained health data analysis model, generating a personalized analysis report, and outputting an analysis result.
2. The method for acquiring and analyzing health data of a resident in an area according to claim 1, wherein the method for acquiring health data of a resident in an area based on the artificial intelligence health robot specifically comprises:
acquiring an acquisition instruction;
verifying the acquisition instruction, and creating or logging in a resident health data account;
and responding to the acquisition instruction, and acquiring the health data of the residents by the artificial intelligent health robot.
3. The method for acquiring and analyzing health data of a resident using an artificial intelligence health robot according to claim 2, wherein the method for acquiring the health data of the resident by the artificial intelligence health robot specifically comprises:
identifying resident basic information;
user sign acquisition is performed through a health acquisition unit;
the resident physical examination information is sent, and the resident physical examination information is uploaded to a health data cloud management platform;
and acquiring a personalized analysis report, displaying the personalized analysis report, and sending an abnormal early warning.
4. The method as claimed in any one of claims 1 to 3, wherein the health data collecting and analyzing method using the artificial intelligence health robot is carried by a front-end intelligence collecting team, and the front-end intelligence collecting team comprises:
the movable digital physical examination vehicle takes a special vehicle as a carrier, integrates various intelligent physical examination devices, and can realize real-time acquisition, transmission and processing of data;
the public health examination workstation supports multi-region synchronous work and simultaneous detection of multiple persons;
family doctor wisdom terminal that can conveniently carry.
5. The health data collection and analysis method using the artificial intelligence health robot according to any one of claims 1 to 3, wherein the health data cloud management platform comprises:
the health data acquisition unit is used for responding to an uploading instruction of the artificial intelligent health robot and acquiring health data of residents in an area;
the health data processing unit loads the health data of residents in the area, and carries out noise reduction, resampling and classification processing on the health data of the residents in the area to form a classified health data set;
and the health data sending unit loads the classified health data set and sends the health data set to the cloud sharing database.
6. The method for health data collection and analysis using an artificial intelligence health robot of claim 5, wherein the method for denoising, resampling and classifying the health data of residents in the area further comprises:
loading the health data of residents in the area;
acquiring a classified evaluation item of resident health data in an area, and discretizing the classified evaluation item to obtain a discretized classified evaluation item;
respectively calculating the association degrees between the resident health data in the single group of areas and the multiple groups of classified evaluation items by adopting a grey association degree method to form an association degree queue;
and loading the association degree queue, judging whether the association degree of the resident health data in the area and the classification evaluation items exceeds a set threshold, and if so, loading the resident health data in the area into at least one group of corresponding classification evaluation items.
7. The method for acquiring and analyzing health data by using the artificial intelligence health robot as claimed in claim 6, wherein the method for establishing the cloud sharing database specifically comprises:
acquiring a cloud sharing database topological structure tree;
loading a health data set and classification evaluation items corresponding to the health data set, and inputting the health data set and the classification evaluation items corresponding to the health data set into a cloud sharing database topological structure tree;
and generating a rendered cloud sharing database.
8. The method for acquiring and analyzing health data by using the artificial intelligence health robot as claimed in claim 7, wherein the method for analyzing the health data analysis model specifically comprises:
loading a cloud sharing database;
calling a real-time health data set, and indexing a historical health data set based on a preset data index format, wherein the historical health data set comprises main associated health data and auxiliary associated health data;
clustering the main associated health data, the auxiliary associated health data and the real-time health data set, acquiring outliers in the health data according to a clustering result, judging the abnormal degree of the outliers, and determining the corresponding real-time health data.
9. The method for acquiring and analyzing health data using an artificial intelligence health robot according to claim 8, wherein the method for analyzing the health data analysis model further comprises:
loading corresponding real-time health data;
extracting real-time health data abnormal diagnosis records in a cloud sharing database, and acquiring medical diagnosis records corresponding to the abnormal diagnosis records;
determining the disease species to be analyzed, analyzing the disease species, and acquiring the hospitalizing information, the treatment information and the rehabilitation nursing information corresponding to the disease species.
10. The method for health data collection and analysis using an artificial intelligence health robot of claim 9, wherein the method for generating the personalized analysis report specifically comprises:
obtaining analysis results, wherein the analysis results comprise a conventional physical examination report, abnormal early warning, intelligent assessment and health guidance;
and pushing the analysis result, and pushing the analysis result to the front-end intelligent acquisition working group, the doctor end and the user end in real time based on the communication protocol.
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