CN111540472A - Intelligent risk assessment system and method for health activities - Google Patents
Intelligent risk assessment system and method for health activities Download PDFInfo
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- CN111540472A CN111540472A CN202010417338.2A CN202010417338A CN111540472A CN 111540472 A CN111540472 A CN 111540472A CN 202010417338 A CN202010417338 A CN 202010417338A CN 111540472 A CN111540472 A CN 111540472A
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- 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
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract
The invention discloses an intelligent risk evaluation system of health activity and an evaluation method thereof, belonging to the technical field of information, the system comprises a keyword search unit, an information input unit, an information transmission unit, a control unit, a man-machine interaction unit, a drive unit, an information processing unit, an information comparison unit and an information storage unit, wherein the control unit is connected with the keyword search unit, the information input unit, the information transmission unit, the drive unit, the information processing unit, the information comparison unit and the information storage unit, in the application file, the risk coefficient of the activity in the normal state is excluded from being displayed only by management, the activity category in the fuzzy state is subjected to extreme comparison by fuzzy algorithm processing, so that the risk coefficient of the activity in the extreme state can be obtained, and then the coefficient is output to a control panel for a user to check, the risk factor for the activity is automatically determined by the user, thereby effectively reducing the risk of developing.
Description
Technical Field
The invention relates to the technical field of information, in particular to an intelligent risk assessment system for health activities and an assessment method thereof.
Background
The health activities can effectively improve the immunity and physical and mental health of people, the requirements of people on the health activities are higher and higher along with social development, and currently, the health activities are not defined clearly, so that some activities in a fuzzy state can be defined wrongly, for example, the health activities in the fuzzy state are defined as unhealthy activities, the unhealthy activities in the fuzzy state are defined as health activities, and finally risks are easily caused.
Disclosure of Invention
This section is for the purpose of summarizing some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. In this section, as well as in the abstract and the title of the invention of this application, simplifications or omissions may be made to avoid obscuring the purpose of the section, the abstract and the title, and such simplifications or omissions are not intended to limit the scope of the invention.
The present invention has been made in view of the above and/or other problems with existing health activity risk assessment.
Therefore, an object of the present invention is to provide an intelligent risk assessment system for health activities and an assessment method thereof, which can assess activities written in a fuzzy state, and then determine whether the activities belong to health activities according to assessment results, thereby reducing risk.
To solve the above technical problem, according to an aspect of the present invention, the present invention provides the following technical solutions:
an intelligent risk assessment system for health activities comprises a keyword retrieval unit, an information input unit, an information transmission unit, a control unit, a man-machine interaction unit, a driving unit, an information processing unit, an information comparison unit and an information storage unit, wherein the keyword retrieval unit, the information input unit, the information transmission unit, the control unit, the driving unit, the information processing unit, the information comparison unit and the information storage unit are all installed in the man-machine interaction unit, the man-machine interaction unit comprises a shell, and a control panel and control keys which are installed outside the shell, the control panel and the control keys are in output connection with the control unit, and the control unit is connected with the keyword retrieval unit, the information input unit, the information transmission unit, the driving unit, the information processing unit, the information comparison unit and the information storage unit.
As a preferable aspect of the intelligent risk assessment system for health activities according to the present invention, wherein: the keyword retrieval unit operates based on a keyword extraction algorithm, the keyword retrieval unit is installed in the human-computer interaction unit, the control unit is connected with the keyword retrieval unit in a bidirectional mode, the information input unit is connected with the control unit in an output mode, the human-computer interaction unit is connected with the information input unit in an output mode, and the information input unit operates based on the human-computer interaction unit.
As a preferable aspect of the intelligent risk assessment system for health activities according to the present invention, wherein: the information transmission unit is a wireless network transmission unit, the information transmission unit is connected with the control unit in a two-way mode, the driving unit is an electric driving system, the driving unit is connected with the control unit and control panels and control keys on the human-computer interaction unit, and the driving unit is connected with the keyword retrieval unit, the information input unit, the information transmission unit, the information processing unit, the information comparison unit and the information storage unit through the control unit.
As a preferable aspect of the intelligent risk assessment system for health activities according to the present invention, wherein: the information processing unit operates based on a fuzzy algorithm, an information comparison unit and an information storage unit, and specifically comprises the following operation steps:
the method comprises the following steps: retrieving the generated activity category in an information storage unit;
step two: when the health activity type is in a fuzzy state, fuzzy processing is carried out through an information processing unit;
step three: carrying out extreme comparison on the processed category information, namely comparing the category information in the health activity category with the category information which is not in the health activity category;
step four: and generating an evaluation value according to the comparison information for the user to judge.
As a preferable aspect of the intelligent risk assessment method for health activities according to the present invention, wherein: the evaluation method is as follows:
the method comprises the following steps: selecting the type of activity by a control panel on the human-computer interaction unit;
step two: selecting a keyword according to the keyword retrieval unit, and retrieving in the storage unit;
step three: selecting whether information processing is needed or not according to the retrieval information;
step four: performing risk assessment according to the generated processing information;
step five: the risk assessment information is output to the control panel for reference by the user.
As a preferable aspect of the intelligent risk assessment method for health activities according to the present invention, wherein: in the second step, when searching for the keyword, the control unit needs to set the threshold of the activity type in the storage unit, that is, set the risk coefficient of the activity type, with 0 to 5 levels in total. The risk factor for a health activity is infinitely close to 0, whereas the radio is close to 5.
As a preferable aspect of the intelligent risk assessment method for health activities according to the present invention, wherein: the specific conditions of the retrieval in the third step are as follows:
when the risk coefficient of the activity type in the storage unit is more than 0 or 5, the risk coefficient is directly output to a control panel for a co-user to check;
when the risk coefficient of the activity type in the storage unit is about 2.5 or the activity type not existing in the storage unit, the specific processing steps are as follows:
the method comprises the following steps: retrieving the generated activity category in an information storage unit;
step two: when the health activity type is in a fuzzy state, fuzzy processing is carried out through an information processing unit;
step three: carrying out extreme comparison on the processed category information, namely comparing the category information in the health activity category with the category information which is not in the health activity category;
step four: and generating an evaluation value according to the comparison information for the user to judge.
Compared with the prior art: at present, health activities are not clearly defined, so that some activities in a fuzzy state are defined by mistake, for example, health activities in the fuzzy state are defined as unhealthy activities, unhealthy activities in the fuzzy state are defined as health activities, and finally risks are easily generated.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the present invention will be described in detail with reference to the accompanying drawings and detailed embodiments, 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 to obtain other drawings without inventive exercise. Wherein:
FIG. 1 is a schematic diagram of a system structure of an intelligent risk assessment system and an assessment method for health activities according to the present invention;
fig. 2 is a schematic flow structure diagram of an intelligent risk assessment system for health activities and an assessment method thereof according to the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described herein, and it will be apparent to those of ordinary skill in the art that the present invention may be practiced without departing from the spirit and scope of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
Next, the present invention will be described in detail with reference to the drawings, wherein for convenience of illustration, the cross-sectional view of the device structure is not enlarged partially according to the general scale, and the drawings are only examples, which should not limit the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
The invention provides an intelligent risk assessment system for health activities, please refer to fig. 1, which comprises a keyword retrieval unit, an information input unit, an information transmission unit, a control unit, a human-computer interaction unit, a driving unit, an information processing unit, an information comparison unit and an information storage unit, the key word retrieval unit, the information input unit, the information transmission unit, the control unit, the driving unit, the information processing unit, the information comparison unit and the information storage unit are all arranged in the man-machine interaction unit, the man-machine interaction unit comprises a shell, a control panel and control keys which are arranged outside the shell, the control panel and the control key output are connected with the control unit, and the control unit is connected with the keyword retrieval unit, the information input unit, the information transmission unit, the driving unit, the information processing unit, the information comparison unit and the information storage unit.
The keyword retrieval unit operates based on a keyword extraction algorithm, the keyword retrieval unit is installed in a human-computer interaction unit, the control unit is connected with the keyword retrieval unit in a bidirectional mode, the information input unit is connected with the control unit in an output mode, the human-computer interaction unit is connected with the information input unit in an output mode, and the information input unit operates based on the human-computer interaction unit;
the keyword extraction algorithm in the application file adopts a supervised extra algorithm, so that the retrieval efficiency can be effectively improved, and the activity risk value can be rapidly obtained.
The information transmission unit is a wireless network transmission unit, the information transmission unit is connected with the control unit in a two-way mode, the driving unit is an electric driving system, the driving unit is connected with the control unit and control panels and control keys on the human-computer interaction unit, and the driving unit is connected with the keyword retrieval unit, the information input unit, the information transmission unit, the information processing unit, the information comparison unit and the information storage unit through the control unit.
The information processing unit operates based on a fuzzy algorithm, an information comparison unit and an information storage unit, and specifically comprises the following operation steps:
the method comprises the following steps: retrieving the generated activity category in an information storage unit;
step two: when the health activity type is in a fuzzy state, fuzzy processing is carried out through an information processing unit;
step three: carrying out extreme comparison on the processed category information, namely comparing the category information in the health activity category with the category information which is not in the health activity category;
step four: and generating an evaluation value according to the comparison information for the user to judge.
The fuzzy algorithm in the information processing unit mainly aims at reducing the activity bias at the intermediate risk value, the fuzzy algorithm can effectively reduce the activity risk bias generation, if the risk value of a certain activity in the information storage unit is 2.4 or 2.6 (biased to the intermediate risk value), the fuzzy algorithm is adopted for operation, the fuzzy algorithm comprises the specific steps of advanced risk coefficient adjustment, risk coefficient comparison and risk coefficient acquisition, according to the method, the risk coefficient acquisition of multiple words can be carried out according to the risk types, the acquired information is made into a fuzzy relation matrix, normalization processing is carried out according to the maximum value method in the matrix, then the matrix is transposed, inference synthesis rules are carried out, the value for risk analysis is distributed to a control point set by an information distribution method, a risk value is obtained.
An intelligent risk assessment method for health activities, please refer to fig. 2, the assessment method is as follows:
the method comprises the following steps: selecting the type of activity by a control panel on the human-computer interaction unit;
step two: selecting a keyword according to the keyword retrieval unit, and retrieving in the storage unit;
step three: selecting whether information processing is needed or not according to the retrieval information;
step four: performing risk assessment according to the generated processing information;
step five: the risk assessment information is output to the control panel for reference by the user.
When the keyword search is performed in the second step, the control unit needs to set the threshold of the activity type in the storage unit, that is, set the risk coefficient of the activity type, with 0 to 5 levels in total. The risk factor for a health activity is infinitely close to 0, whereas the radio is close to 5.
The specific conditions of the retrieval in the third step are as follows:
when the risk coefficient of the activity type in the storage unit is more than 0 or 5, the risk coefficient is directly output to a control panel for a co-user to check;
when the risk coefficient of the activity type in the storage unit is about 2.5 or the activity type not existing in the storage unit, the specific processing steps are as follows:
the method comprises the following steps: retrieving the generated activity category in an information storage unit;
step two: when the health activity type is in a fuzzy state, fuzzy processing is carried out through an information processing unit;
step three: carrying out extreme comparison on the processed category information, namely comparing the category information in the health activity category with the category information which is not in the health activity category;
step four: and generating an evaluation value according to the comparison information for the user to judge.
While the invention has been described above with reference to an embodiment, various modifications may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In particular, the various features of the disclosed embodiments of the invention may be used in any combination, provided that no structural conflict exists, and the combinations are not exhaustively described in this specification merely for the sake of brevity and resource conservation. Therefore, it is intended that the invention not be limited to the particular embodiments disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.
Claims (7)
1. An intelligent risk assessment system for health activities, characterized by: the system comprises a keyword retrieval unit, an information input unit, an information transmission unit, a control unit, a human-computer interaction unit, a driving unit, an information processing unit, an information comparison unit and an information storage unit, wherein the keyword retrieval unit, the information input unit, the information transmission unit, the control unit, the driving unit, the information processing unit, the information comparison unit and the information storage unit are all arranged in the human-computer interaction unit, the human-computer interaction unit comprises a shell, and a control panel and a control key which are arranged outside the shell, the control panel and the control key are in output connection with the control unit, and the control unit is connected with the keyword retrieval unit, the information input unit, the information transmission unit, the driving unit, the information processing unit, the information comparison unit and the information storage unit.
2. The intelligent risk assessment system for health activities of claim 1, wherein: the keyword retrieval unit operates based on a keyword extraction algorithm, the keyword retrieval unit is installed in the human-computer interaction unit, the control unit is connected with the keyword retrieval unit in a bidirectional mode, the information input unit is connected with the control unit in an output mode, the human-computer interaction unit is connected with the information input unit in an output mode, and the information input unit operates based on the human-computer interaction unit.
3. The intelligent risk assessment system for health activities of claim 1, wherein: the information transmission unit is a wireless network transmission unit, the information transmission unit is connected with the control unit in a two-way mode, the driving unit is an electric driving system, the driving unit is connected with the control unit and control panels and control keys on the human-computer interaction unit, and the driving unit is connected with the keyword retrieval unit, the information input unit, the information transmission unit, the information processing unit, the information comparison unit and the information storage unit through the control unit.
4. The intelligent risk assessment system for health activities of claim 1, wherein: the information processing unit operates based on a fuzzy algorithm, an information comparison unit and an information storage unit, and specifically comprises the following operation steps:
the method comprises the following steps: retrieving the generated activity category in an information storage unit;
step two: when the health activity type is in a fuzzy state, fuzzy processing is carried out through an information processing unit;
step three: carrying out extreme comparison on the processed category information, namely comparing the category information in the health activity category with the category information which is not in the health activity category;
step four: and generating an evaluation value according to the comparison information for the user to judge.
5. The intelligent risk assessment method for health activities according to any one of claims 1-4, characterized in that: the evaluation method is as follows:
the method comprises the following steps: selecting the type of activity by a control panel on the human-computer interaction unit;
step two: selecting a keyword according to the keyword retrieval unit, and retrieving in the storage unit;
step three: selecting whether information processing is needed or not according to the retrieval information;
step four: performing risk assessment according to the generated processing information;
step five: the risk assessment information is output to the control panel for reference by the user.
6. The intelligent risk assessment method for health activities of claim 5, wherein: in the second step, when searching for the keyword, the control unit needs to set the threshold of the activity type in the storage unit, that is, set the risk coefficient of the activity type, with 0 to 5 levels in total. The risk factor for a health activity is infinitely close to 0, whereas the radio is close to 5.
7. The intelligent risk assessment method for health activities of claim 5, wherein: the specific conditions of the retrieval in the third step are as follows:
when the risk coefficient of the activity type in the storage unit is more than 0 or 5, the risk coefficient is directly output to a control panel for a co-user to check;
when the risk factor of the activity type in the storage unit is about 2.5 or the activity type not existing in the storage unit, the specific processing steps are the same as those in claim 4.
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Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004362451A (en) * | 2003-06-06 | 2004-12-24 | Nippon Telegr & Teleph Corp <Ntt> | Method and system for displaying retrieving keyword information, and retrieving keyword information display program |
| JP2009176058A (en) * | 2008-01-24 | 2009-08-06 | Tokio Marine & Nichido Fire Insurance Co Ltd | Risk evaluation slip generation system |
| CN102467609A (en) * | 2010-10-29 | 2012-05-23 | 大荣优比泰克有限公司 | Media recommending system based on health index |
| CN103093103A (en) * | 2013-01-23 | 2013-05-08 | 西安阔途软件科技有限公司 | Multi-disease health risk factor evaluating system and method |
| CN104572887A (en) * | 2014-12-24 | 2015-04-29 | 刘永健 | Method and system for retrieving product information |
| CN106295252A (en) * | 2016-08-18 | 2017-01-04 | 杭州布理岚柏科技有限公司 | Search method for gene prod |
| CN106326654A (en) * | 2016-08-24 | 2017-01-11 | 北京辛诺创新科技有限公司 | Big data cloud analysis-based health prediction system, intelligent terminal and server |
| CN106407643A (en) * | 2016-08-03 | 2017-02-15 | 无锡金世纪国民体质与健康研究有限公司 | Method for establishing health risk assessment system |
| CN106446071A (en) * | 2016-09-07 | 2017-02-22 | 知识产权出版社有限责任公司 | Information processing apparatus and method |
| CN107357931A (en) * | 2017-07-29 | 2017-11-17 | 合肥千奴信息科技有限公司 | A kind of intelligence system of big data cognitive Decision |
| CN108074648A (en) * | 2016-11-18 | 2018-05-25 | 株式会社倍乐生思泰服务 | Service assistance system, service householder method and program |
| CN108206058A (en) * | 2016-12-19 | 2018-06-26 | 平安科技（深圳）有限公司 | Human body comprehensive health risk Forecasting Methodology and system |
| CN110033202A (en) * | 2019-04-22 | 2019-07-19 | 广东电网有限责任公司 | A kind of methods of risk assessment and assessment system of power business system |
| CN110580312A (en) * | 2019-08-30 | 2019-12-17 | 腾讯科技（深圳）有限公司 | Data query method and device and computer readable storage medium |
| CN110739082A (en) * | 2019-10-15 | 2020-01-31 | 广东电网有限责任公司 | occupational health risk management and control measure evaluation method and related device |
| CN110895536A (en) * | 2019-11-07 | 2020-03-20 | 国网浙江杭州市富阳区供电有限公司 | Big data-based power information retrieval method and power information retrieval device |
-
2020
- 2020-05-18 CN CN202010417338.2A patent/CN111540472B/en active Active
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004362451A (en) * | 2003-06-06 | 2004-12-24 | Nippon Telegr & Teleph Corp <Ntt> | Method and system for displaying retrieving keyword information, and retrieving keyword information display program |
| JP2009176058A (en) * | 2008-01-24 | 2009-08-06 | Tokio Marine & Nichido Fire Insurance Co Ltd | Risk evaluation slip generation system |
| CN102467609A (en) * | 2010-10-29 | 2012-05-23 | 大荣优比泰克有限公司 | Media recommending system based on health index |
| CN103093103A (en) * | 2013-01-23 | 2013-05-08 | 西安阔途软件科技有限公司 | Multi-disease health risk factor evaluating system and method |
| CN104572887A (en) * | 2014-12-24 | 2015-04-29 | 刘永健 | Method and system for retrieving product information |
| CN106407643A (en) * | 2016-08-03 | 2017-02-15 | 无锡金世纪国民体质与健康研究有限公司 | Method for establishing health risk assessment system |
| CN106295252A (en) * | 2016-08-18 | 2017-01-04 | 杭州布理岚柏科技有限公司 | Search method for gene prod |
| CN106326654A (en) * | 2016-08-24 | 2017-01-11 | 北京辛诺创新科技有限公司 | Big data cloud analysis-based health prediction system, intelligent terminal and server |
| CN106446071A (en) * | 2016-09-07 | 2017-02-22 | 知识产权出版社有限责任公司 | Information processing apparatus and method |
| CN108074648A (en) * | 2016-11-18 | 2018-05-25 | 株式会社倍乐生思泰服务 | Service assistance system, service householder method and program |
| CN108206058A (en) * | 2016-12-19 | 2018-06-26 | 平安科技（深圳）有限公司 | Human body comprehensive health risk Forecasting Methodology and system |
| CN107357931A (en) * | 2017-07-29 | 2017-11-17 | 合肥千奴信息科技有限公司 | A kind of intelligence system of big data cognitive Decision |
| CN110033202A (en) * | 2019-04-22 | 2019-07-19 | 广东电网有限责任公司 | A kind of methods of risk assessment and assessment system of power business system |
| CN110580312A (en) * | 2019-08-30 | 2019-12-17 | 腾讯科技（深圳）有限公司 | Data query method and device and computer readable storage medium |
| CN110739082A (en) * | 2019-10-15 | 2020-01-31 | 广东电网有限责任公司 | occupational health risk management and control measure evaluation method and related device |
| CN110895536A (en) * | 2019-11-07 | 2020-03-20 | 国网浙江杭州市富阳区供电有限公司 | Big data-based power information retrieval method and power information retrieval device |
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|---|---|
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