{"title":"通过设计预测分析模型预防糖尿病","authors":"Lindita Loku, B. Fetaji, M. Fetaji","doi":"10.1109/HORA49412.2020.9152894","DOIUrl":null,"url":null,"abstract":"The focus of the research study was analyses of predictive model for prognosis and prediction of type 2 diabetes mellitus (DM) that are investigated during the study. Diabetes mellitus is thought of as one of the vital deadliest and persistent sicknesses which reasons an build up in blood sugar. Many occurrences of death and different health complications happen if diabetes mellitus stays untreated and unidentified. The research study is therefore focused in devising analytical predictive model that can guide decisions of healthcare people more effectively and provide insights into the illness. We have analyzed the Artificial Neural Network (ANN) model and further improved it by adding additional impacting factors and assessing the attributes. In conclusion, the developed machine learning model for the prediction and detection of diabetes is important as the condition continues to increase in prevalence worldwide while simultaneously increasing its economic burden. Insights and guidelines are discussed and recommendations are provided.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Prevention Of Diabetes By Devising A Prediction Analytics Model\",\"authors\":\"Lindita Loku, B. Fetaji, M. Fetaji\",\"doi\":\"10.1109/HORA49412.2020.9152894\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The focus of the research study was analyses of predictive model for prognosis and prediction of type 2 diabetes mellitus (DM) that are investigated during the study. Diabetes mellitus is thought of as one of the vital deadliest and persistent sicknesses which reasons an build up in blood sugar. Many occurrences of death and different health complications happen if diabetes mellitus stays untreated and unidentified. The research study is therefore focused in devising analytical predictive model that can guide decisions of healthcare people more effectively and provide insights into the illness. We have analyzed the Artificial Neural Network (ANN) model and further improved it by adding additional impacting factors and assessing the attributes. In conclusion, the developed machine learning model for the prediction and detection of diabetes is important as the condition continues to increase in prevalence worldwide while simultaneously increasing its economic burden. Insights and guidelines are discussed and recommendations are provided.\",\"PeriodicalId\":166917,\"journal\":{\"name\":\"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HORA49412.2020.9152894\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HORA49412.2020.9152894","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prevention Of Diabetes By Devising A Prediction Analytics Model
The focus of the research study was analyses of predictive model for prognosis and prediction of type 2 diabetes mellitus (DM) that are investigated during the study. Diabetes mellitus is thought of as one of the vital deadliest and persistent sicknesses which reasons an build up in blood sugar. Many occurrences of death and different health complications happen if diabetes mellitus stays untreated and unidentified. The research study is therefore focused in devising analytical predictive model that can guide decisions of healthcare people more effectively and provide insights into the illness. We have analyzed the Artificial Neural Network (ANN) model and further improved it by adding additional impacting factors and assessing the attributes. In conclusion, the developed machine learning model for the prediction and detection of diabetes is important as the condition continues to increase in prevalence worldwide while simultaneously increasing its economic burden. Insights and guidelines are discussed and recommendations are provided.