CN109300546A - A kind of individual sub-health state appraisal procedure based on big data and artificial intelligence - Google Patents
A kind of individual sub-health state appraisal procedure based on big data and artificial intelligence Download PDFInfo
- Publication number
- CN109300546A CN109300546A CN201811437841.3A CN201811437841A CN109300546A CN 109300546 A CN109300546 A CN 109300546A CN 201811437841 A CN201811437841 A CN 201811437841A CN 109300546 A CN109300546 A CN 109300546A
- Authority
- CN
- China
- Prior art keywords
- health
- sub
- model
- health state
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- General Health & Medical Sciences (AREA)
- Data Mining & Analysis (AREA)
- Epidemiology (AREA)
- Biomedical Technology (AREA)
- Primary Health Care (AREA)
- Databases & Information Systems (AREA)
- Pathology (AREA)
- Nutrition Science (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The individual sub-health state appraisal procedure based on big data and artificial intelligence that the invention discloses a kind of, including establishing inferior health assessment initial model based on evidence-based medicine EBM, epidemiology, Dietary survey, nutritional intervention data, using the diet of large sample crowd, movement and sign information analysis statistical result revision inferior health assessment models parameter and carry out cross validation, personal information input model obtains sub-health state score and interprets report, persistently calculates optimization inferior health assessment models using individual information accumulation big data.The model provides solution for individual sub-health state assessment, it can realize that real-time tracking is assessed using intelligent mobile terminal, wearable device, personalized, scientific, visual sub-health state and scale evaluation service are provided for resident, facilitate resident to understand the functional state of itself, and can establish long-term health archives.
Description
Technical field
The present invention relates to a kind of sub-health state appraisal procedure more particularly to a kind of based on big data and artificial intelligence
Body sub-health state appraisal procedure, belongs to health care technical field.
Background technique
In recent years, with the progress of life science, people are more and more deep to the understanding of vital movement process, accordingly
Improve the cognition and intervention techniques level for occurring to disease, developing.With the development of evidence-based medicine EBM, people to disease criterion and
Kinds of Diseases determine to achieve many common recognitions, clearly define and divide standard so that having to disease, be conducive to medical treatment working
Person selects suitable means to intervene disease, is allowed to that disease development is delayed even to restore to non-disease conditions.It is well known that disease
A slow, progressive process, be from health status to sub-health state, then arrive disease a process.At present
In medical health field, there is no a clear feasible determination method and measurement standards for health and inferior health boundary line, so that people
To oneself, whether sub-health state is apparent or even inferior health degree cannot also understand, so as to cause prevention disease often at
For a kind of empty talk.In addition, the biosystem that human body is complicated as one, precise structure, the coordinating and unifying are to remain good strong
Health state, but in place of the details of specific physiological activity everyone there may be differences, such as height, blood pressure, metabolic rate
Etc., it is reflected in everyone normal condition physical signs not fully.Therefore, to the differentiation of sub-health state and degree
Existing group's common feature and parameter index, while also needing to embody the difference of individuation.
In fact, understanding of the people to self-disease or non-disease conditions (including health status and sub-health state) at present
It is reported from regularly medical institutions' physical examination, includes: 1, reference standard from medical conditions differentiation scope there are main problem, no
The difference degree between the comprehensive health of examinee or sub-health state and degree, and individual and population parameter can be assessed；2,
Physical examination often ignores the background difference of examinee individual, such as diet, daily life, heredity, geography, age etc., nothing
Method understand it is identical/close to the individual under background severity and between group, the difference condition of physiological status, and thus know and really
Surely improve direction.
Therefore, the judgment method for establishing the sub-health state and degree with individualized feature reverses inferior health for individual
State and prevention disease are of great significance.
Summary of the invention
The individual sub-health state appraisal procedure based on big data and artificial intelligence that the purpose of the present invention is to provide a kind of,
Method specifically includes the following steps:
(1) inferior health assessment is established initially based on evidence-based medicine EBM, epidemiology, Dietary survey, nutritional intervention data
Model, model expression S=A1F1+A2F2+A3F3+…+AiFi, wherein S is inferior health score, and Ai is i-th of Factor Weight system
Number, Fi are i-th of factor；
(2) information collection end group is no less than diet, movement and the sign information of 1000 people in collection rule acquisition, using more
Dimension statistics and regression analysis, clustering count each index median numerical value, distributed area and diet, movement and sign and believe
The correlation of breath；
(3) according to the correlation results of diet, movement and sign information, using analytic hierarchy process (AHP), comprehensive scoring method, it is main at
Divide the weight coefficient of analytic approach and the Gray Association Analysis revision models factor, with neural network analysis method, Integrated Algorithm, returns and divide
Analysis, decision Tree algorithms and Mote Carlo model obtain all factors of expression model and the relational model of single factor values；
It (4) can using K times of cross-validation method (K-fold cross validation) verifying inferior health assessment models quality
By property, model prediction dependability parameter > 0.5 is acceptable, acquisition inferior health assessment correction model；
(5) information collection end inputs individual information and assesses correction model to inferior health, obtains personal inferior health comprehensive score
And interpret report；
(6) (2) in the big-sample data of the personal information data steps for importing (2) in above-mentioned (5) step, will be repeated to arrive
(4) step, lasting calculation optimization inferior health assessment models.
Further, in the assessment models of step (1), the weight coefficient of all factors adds up to 1, and the factor includes diet fortune
Reason element, sign information factor.
Further, in step (2), the collection rule includes acquisition time, information type and frequency.
Further, personal information source includes that physical examination data, questionnaire survey data, intelligence wearable are set in step (5)
Standby detection data.
Further, it is excellent to carry out duration to inferior health score evaluation model by the accumulation of individual data items for step (6)
Change, realizes more personalized inferior health assessment.
Compared with prior art, the beneficial effect of technical solution of the present invention is: 1, using newest evidence-based medicine EBM,
Epidemiology, Dietary survey and crowd intervene scientific big data can more fully, science, objectively obtain inferior health
Influence factor and measurement index, so that inferior health score model is more representative；2, using the integrated data of no less than 1000 people,
Optimization and verifying inferior health score model, and Continuous optimization model is accumulated using individual data items, so that inferior health assessment models are more
It is accurate；3, by individual input data, using inferior health score assessment models, so that individual will be seen that it between group
Difference degree in comprehensive factor dimension, rather than only evaluated whether with medical guidelines in morbid state；4, pass through individual
The continuous accumulation of data, Continuous optimization inferior health score model, finally makes inferior health assessment models evolve as personalization
Accurate model, it is meant that everyone health and inferior health parameter be different；5, based on big data and artificial intelligence
Individual sub-health state appraisal procedure takes full advantage of mobile, intelligence, convenient and fast Internet technology advantage, allows individual fast
Speed knows the state and inferior health change curve of inferior health, easily establishes the thought of prevention of diseae.
Detailed description of the invention
The individual inferior health score appraisal procedure step schematic diagram of Fig. 1 embodiment of the present invention 1.
Specific embodiment
The attached figures are only used for illustrative purposes and cannot be understood as limitating the patent.
For those skilled in the art, certain known features and its explanation may be omitted, amplify or contract in attached drawing
It is small to will be understood by.
Technical scheme is described further with reference to the accompanying drawings and examples.
Embodiment 1
As shown in Figure 1, a kind of individual inferior health analysis and assessment method based on big data and artificial intelligence, including following step
It is rapid:
(1) inferior health assessment is established initially based on evidence-based medicine EBM, epidemiology, Dietary survey, nutritional intervention data
Model, model expression S=A1F1+A2F2+A3F3+…+AiFi, wherein S is inferior health score, and Ai is i-th of Factor Weight system
Number, Fi are i-th of factor；
(2) information collection end group is no less than diet, movement and the sign information of 1000 people in collection rule acquisition, using more
Dimension statistics and regression analysis, clustering count each index median numerical value, distributed area and diet, movement and sign and believe
The correlation of breath；
(3) according to the correlation results of diet, movement and sign information, using analytic hierarchy process (AHP), comprehensive scoring method, it is main at
Divide the weight coefficient of analytic approach and the Gray Association Analysis revision models factor, global neurological Network Analysis Method, decision Tree algorithms, collection
All factors of expression model and the relational model of single factor values are obtained at algorithm and Mote Carlo model；
It (4) can using K times of cross-validation method (K-fold cross validation) verifying inferior health assessment models quality
By property, model prediction dependability parameter > 0.5 is acceptable, acquisition inferior health assessment correction model；
(5) information collection end inputs individual information and assesses correction model to inferior health, obtains personal inferior health comprehensive score
And interpret report；
(6) (2) in the big-sample data of the personal information data steps for importing (2) in above-mentioned (5) step, will be repeated to arrive
(4) step, lasting calculation optimization inferior health assessment models.
In specific implementation process of the present invention, data described in step (1) include evidence-based medicine EBM, epidemiology, diet
The lasting open achievement that nutrition survey, lifestyle modification are studied, Optimized model impact factor and weight coefficient and score knot
The interpretation of fruit updates.
In specific implementation process of the present invention, 1000 personal datas collected in step (2), including questionnaire result, physical examination knot
Fruit, wearable device it is regular transmission as a result, and according to the age, gender, eating habit, weight carry out the first hierarchical data classification,
Then carry out a variety of statistical analysis of step (3).
In the specific implementation process, the information from questionnaire, health examination, wearable device is stored in and builds on cloud
In the database of server, database platform provides API (application programming interfaces) towards all users, including physical examination mechanism, a
People, intelligent mobile terminal, sign detection device, wearable device.Mobile terminal, detection device and the wearable device tool
There is wireless communication function, preset the sign information of acquisition individual and obtain the period of feedback information, for example, can pass through
Mobile terminal setting reminds before 10 points user to input the diet and motion information on the same day at night daily；The wearable device
It can be blood pressure instrument, BOLD contrast, rhythm of the heart monitor etc., acquisition time is divided into early, middle and late three periods.The information of acquisition can
To be temporarily stored on mobile terminal and wearable device, periodically uploaded in cloud database by wireless communication networks.Pass through
The continuous accumulation of individuation data information carries out Continuous optimization to inferior health assessment models, the accuracy of model is improved, to mention
Accuracy of the height to personal inferior health assessment result.
In the specific implementation process, in result output, using visual supervision statistical analysis technique, to open up
Show the difference and degree between group that is personal and constituting inferior health assessment models, and exports corresponding report and interpret.It is personal
After taking inferior health assessment report, relevant medical health expert can be seeked advice from, with the accuracy of definitive result and is improved
It is recommended that.By continuing, regularly personal sub-health state is assessed, and establishes personal health electronic record, and tracking inferior health variation is bent
Line, while being also aware that itself functional state and the deviation situation of a wide range of crowd.
Obviously, the above embodiment of the present invention be only to clearly illustrate example of the present invention, and not be pair
The restriction of embodiments of the present invention may be used also on the basis of the above description for those of ordinary skill in the art
To make other variations or changes in different ways, all embodiments can not be exhaustive here, it is all to belong to this hair
The obvious changes or variations that bright technical solution is extended out are still in the scope of protection of the present invention.
Claims (5)
1. a kind of individual sub-health state appraisal procedure based on big data and artificial intelligence, which is characterized in that method include with
Lower step:
(1) inferior health assessment initial model is established based on evidence-based medicine EBM, epidemiology, Dietary survey, nutritional intervention data,
Model expression is S=A1F1+A2F2+A3F3+…+AiFi, wherein S is inferior health score, and Ai is i-th of Factor Weight coefficient, Fi
For i-th of factor；
(2) information collection end group is no less than diet, movement and the sign information of 1000 people in collection rule acquisition, is united using multidimensional
Meter and regression analysis, clustering count each index median numerical value, distributed area and diet, movement and sign information
Correlation；
(3) according to the correlation results of diet, movement and sign information, analytic hierarchy process (AHP), comprehensive scoring method, principal component point are utilized
The weight coefficient of analysis method and the Gray Association Analysis revision models factor, with neural network analysis method, Integrated Algorithm, regression analysis,
Decision Tree algorithms and Mote Carlo model obtain all factors of expression model and the relational model of single factor values；
(4) inferior health assessment models reliable in quality is verified using K times of cross-validation method (K-fold cross validation)
Property, model prediction dependability parameter > 0.5 is acceptable, acquisition inferior health assessment correction model；
(5) information collection end inputs individual information and assesses correction model to inferior health, obtains personal inferior health comprehensive score and solution
It reads the newspaper announcement；
(6) (2) in the big-sample data of the personal information data steps for importing (2) in above-mentioned (5) step, will be repeated and arrives (4) step
Suddenly, lasting calculation optimization inferior health assessment models.
2. the sub-health state appraisal procedure according to claim 1 based on big data and artificial intelligence, which is characterized in that
In the assessment models of step (1), the weight coefficient of all factors adds up to 1；The factor include diet exercise factor, sign information because
Element.
3. the sub-health state appraisal procedure according to claim 1 based on big data and artificial intelligence, which is characterized in that
Collection rule described in step (2) includes acquisition time, information type and frequency.
4. the sub-health state appraisal procedure according to claim 1 based on big data and artificial intelligence, which is characterized in that
Individual information source includes physical examination data, questionnaire survey data, the detection data of intelligent wearable device in step (5).
5. the sub-health state appraisal procedure according to claim 1-4 based on big data and artificial intelligence is a
Application in the assessment of body sub-health state.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811437841.3A CN109300546A (en) | 2018-11-28 | 2018-11-28 | A kind of individual sub-health state appraisal procedure based on big data and artificial intelligence |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811437841.3A CN109300546A (en) | 2018-11-28 | 2018-11-28 | A kind of individual sub-health state appraisal procedure based on big data and artificial intelligence |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109300546A true CN109300546A (en) | 2019-02-01 |
Family
ID=65141333
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811437841.3A Pending CN109300546A (en) | 2018-11-28 | 2018-11-28 | A kind of individual sub-health state appraisal procedure based on big data and artificial intelligence |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109300546A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110782992A (en) * | 2019-10-31 | 2020-02-11 | 刘剑 | Intelligent implementation method and system for quantitative evaluation of rehabilitation effect based on electrocardiosignals |
| CN112435749A (en) * | 2020-12-01 | 2021-03-02 | 大连理工江苏研究院有限公司 | Intelligent human body sub-health assessment system based on big data |
| CN114881177A (en) * | 2022-06-30 | 2022-08-09 | 深圳市前海高新国际医疗管理有限公司 | Nutritional health data acquisition system based on Internet of things technology |
-
2018
- 2018-11-28 CN CN201811437841.3A patent/CN109300546A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110782992A (en) * | 2019-10-31 | 2020-02-11 | 刘剑 | Intelligent implementation method and system for quantitative evaluation of rehabilitation effect based on electrocardiosignals |
| CN112435749A (en) * | 2020-12-01 | 2021-03-02 | 大连理工江苏研究院有限公司 | Intelligent human body sub-health assessment system based on big data |
| CN114881177A (en) * | 2022-06-30 | 2022-08-09 | 深圳市前海高新国际医疗管理有限公司 | Nutritional health data acquisition system based on Internet of things technology |
| CN114881177B (en) * | 2022-06-30 | 2022-10-11 | 深圳市前海高新国际医疗管理有限公司 | Nutritional health data acquisition system based on Internet of things technology |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP3566231B1 (en) | Apparatus and method for triggering a fall risk alert to a person | |
| CN109545328A (en) | A kind of individual inferior health interference method and system based on big data and artificial intelligence | |
| CN102274022B (en) | Sleep state monitoring method based on electroencephalogram signals | |
| CN107334466A (en) | A kind of apparatus and method of wearable chronic disease intelligent monitoring and early warning | |
| CN102056541B (en) | Detection of hypokinetic and/or hyperkinetic states | |
| CN109087706B (en) | Human health assessment method and system based on sleep big data | |
| CN109119130A (en) | A kind of big data based on cloud computing is health management system arranged and method | |
| CN110584601B (en) | Old man cognitive function monitoring and evaluation system | |
| CN109285606A (en) | A kind of health control method and system based on big data intelligent algorithm | |
| CN109256212A (en) | Bone health assessment models construction method, device, equipment, medium and appraisal procedure | |
| CN105342562A (en) | Monitoring method and monitoring system | |
| CN104287706A (en) | Human health state real-time monitoring, diagnosis and treatment recommendation system | |
| CN109300546A (en) | A kind of individual sub-health state appraisal procedure based on big data and artificial intelligence | |
| RU2712395C1 (en) | Method for issuing recommendations for maintaining a healthy lifestyle based on daily user activity parameters automatically tracked in real time, and a corresponding system (versions) | |
| CN110390565A (en) | The method and system of intelligent gateway adaptive management are realized by AI edge calculations | |
| CN105279362A (en) | Personal health monitoring system | |
| CN106777909A (en) | Gestational period health risk assessment system | |
| CN109260566A (en) | Enhance sleep technology using shadow casting technique | |
| CN110911018A (en) | Human health data acquisition system and health monitoring method based on cloud computing | |
| CN113782208A (en) | Family health assessment and intervention system based on intelligent rehabilitation equipment | |
| CN110136822A (en) | A kind of community medicine intelligence management-control method of household wearable device | |
| CN114068042A (en) | Health management platform and management method based on wearable intelligent terminal | |
| Gan et al. | Human-computer interaction based interface design of intelligent health detection using PCANet and multi-sensor information fusion | |
| CN114334158A (en) | Monitoring management method and system based on Internet of things | |
| CN110473631A (en) | Intelligent sleep monitoring method and system based on real world research |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20190201 |