{"title":"使用时间序列分析的卫生保健管理系统","authors":"Shubhangu Shukla, Pulkit Singh, Narayan Neopane, Rishabh","doi":"10.1109/ISCON47742.2019.9036150","DOIUrl":null,"url":null,"abstract":"The paper proposes a technique for risk prediction with graph-based proofs so as to observe and monitor the progress of a developing situation in the field of health. Making an automated system which will help to predict various health parameters of a host remotely is our primary objective. Providing a way to predict the future body temperature, pulse rate, haemoglobin, systolic and diastolic pressure with the help of an existing data set record, in an optimized manner is our primary concern using which we can forecast the health of a patient. Using the collected data with the help of a built-in framework to detect future health hazards is our main objective. Forecasting the health condition is being done by using Time series algorithm to predict body temperature, pulse rate, haemoglobin, systolic and diastolic pressure of the host patient, in an efficient manner. The errors generated for the forecast values are compared using various error evaluation techniques.","PeriodicalId":124412,"journal":{"name":"2019 4th International Conference on Information Systems and Computer Networks (ISCON)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Health Care Management System Using Time Series Analysis\",\"authors\":\"Shubhangu Shukla, Pulkit Singh, Narayan Neopane, Rishabh\",\"doi\":\"10.1109/ISCON47742.2019.9036150\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper proposes a technique for risk prediction with graph-based proofs so as to observe and monitor the progress of a developing situation in the field of health. Making an automated system which will help to predict various health parameters of a host remotely is our primary objective. Providing a way to predict the future body temperature, pulse rate, haemoglobin, systolic and diastolic pressure with the help of an existing data set record, in an optimized manner is our primary concern using which we can forecast the health of a patient. Using the collected data with the help of a built-in framework to detect future health hazards is our main objective. Forecasting the health condition is being done by using Time series algorithm to predict body temperature, pulse rate, haemoglobin, systolic and diastolic pressure of the host patient, in an efficient manner. The errors generated for the forecast values are compared using various error evaluation techniques.\",\"PeriodicalId\":124412,\"journal\":{\"name\":\"2019 4th International Conference on Information Systems and Computer Networks (ISCON)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 4th International Conference on Information Systems and Computer Networks (ISCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCON47742.2019.9036150\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 4th International Conference on Information Systems and Computer Networks (ISCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCON47742.2019.9036150","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Health Care Management System Using Time Series Analysis
The paper proposes a technique for risk prediction with graph-based proofs so as to observe and monitor the progress of a developing situation in the field of health. Making an automated system which will help to predict various health parameters of a host remotely is our primary objective. Providing a way to predict the future body temperature, pulse rate, haemoglobin, systolic and diastolic pressure with the help of an existing data set record, in an optimized manner is our primary concern using which we can forecast the health of a patient. Using the collected data with the help of a built-in framework to detect future health hazards is our main objective. Forecasting the health condition is being done by using Time series algorithm to predict body temperature, pulse rate, haemoglobin, systolic and diastolic pressure of the host patient, in an efficient manner. The errors generated for the forecast values are compared using various error evaluation techniques.