{"title":"基于人工智能的疾病风险判定及预防措施辅助系统","authors":"S. Maleki, Nasser Jazdi-Motlagh","doi":"10.54941/ahfe1001102","DOIUrl":null,"url":null,"abstract":"Prevention of widespread diseases can make an important contribution to improving the quality of human life. Furthermore, disease prevention can serve to avoid future demands for medical rehabilitation due to demographic change. In this paper, a literature review on the state of the art in disease prevention through machine learning will be presented first. Subsequently, it was concluded that no previous applications have focused on determining the extent of the influencing factors on the risk of disease and thus identifying preventive measures to reduce the risk of disease. To address this research gap, this paper presents a concept for generating a personalized prediction model for a given disease, using machine learning algorithms for the automated analysis of a wide range of input data. To realize this concept, an assistance system is implemented be presented, which includes prediction models for the three diseases cold, hypertension and hypercholesterolemia to determine disease risks and preventive measures. After entering the user's health data, the assistance system determines the risk for each disease and the preventive measures to reduce the disease risks. Thereafter, the evaluation of the assistance system is presented by testing it on 5 people who used it daily for 4 months.","PeriodicalId":116806,"journal":{"name":"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An AI-based Assistance System for Determining the Risk of Disease and for Preventive Measures\",\"authors\":\"S. Maleki, Nasser Jazdi-Motlagh\",\"doi\":\"10.54941/ahfe1001102\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Prevention of widespread diseases can make an important contribution to improving the quality of human life. Furthermore, disease prevention can serve to avoid future demands for medical rehabilitation due to demographic change. In this paper, a literature review on the state of the art in disease prevention through machine learning will be presented first. Subsequently, it was concluded that no previous applications have focused on determining the extent of the influencing factors on the risk of disease and thus identifying preventive measures to reduce the risk of disease. To address this research gap, this paper presents a concept for generating a personalized prediction model for a given disease, using machine learning algorithms for the automated analysis of a wide range of input data. To realize this concept, an assistance system is implemented be presented, which includes prediction models for the three diseases cold, hypertension and hypercholesterolemia to determine disease risks and preventive measures. After entering the user's health data, the assistance system determines the risk for each disease and the preventive measures to reduce the disease risks. Thereafter, the evaluation of the assistance system is presented by testing it on 5 people who used it daily for 4 months.\",\"PeriodicalId\":116806,\"journal\":{\"name\":\"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54941/ahfe1001102\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54941/ahfe1001102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An AI-based Assistance System for Determining the Risk of Disease and for Preventive Measures
Prevention of widespread diseases can make an important contribution to improving the quality of human life. Furthermore, disease prevention can serve to avoid future demands for medical rehabilitation due to demographic change. In this paper, a literature review on the state of the art in disease prevention through machine learning will be presented first. Subsequently, it was concluded that no previous applications have focused on determining the extent of the influencing factors on the risk of disease and thus identifying preventive measures to reduce the risk of disease. To address this research gap, this paper presents a concept for generating a personalized prediction model for a given disease, using machine learning algorithms for the automated analysis of a wide range of input data. To realize this concept, an assistance system is implemented be presented, which includes prediction models for the three diseases cold, hypertension and hypercholesterolemia to determine disease risks and preventive measures. After entering the user's health data, the assistance system determines the risk for each disease and the preventive measures to reduce the disease risks. Thereafter, the evaluation of the assistance system is presented by testing it on 5 people who used it daily for 4 months.