{"title":"基于蒙特卡罗算法的远程咨询持续监测预测和降低2型糖尿病并发症的风险水平","authors":"H. Nieto-Chaupis","doi":"10.1109/COLCACI.2018.8484853","DOIUrl":null,"url":null,"abstract":"We present a computer-based eHealth system expected to provide tele-consults aimed to reduce complications due to the diabetes disease in adult population mainly between 30 and 60 years old. The software of the tele-consultations system which is essentially based in probabilities and entirely based in the Monte Carlo technology whose main philosophy: accept or reject, This stochastic computing method is supported with a mathematical model which is build through acquired data and experience that allows us to model and carry out predictions on the glucose’s values in time within a certain statistical error. The idea behind of this eHealth system is the rapid identification of those people with a potential risk to acquire complications derived from the high values of glucose in time. The conclusion derived from this computer-based study is that of the opportune intervention derived from the tele-consultations might alleviate and to improve the diabetes treatment by employing simple mobile phones and minimal software applications. We illustrated the prospective implementation of this tele-care system with simulations for people with an old diagnosis of diabetes and demonstrating the prospective role o these eHealth systems aimed to improve the quality of life in the middle and long term. From a combined sample 3 from 4 diabetes patients might be keeping under control their glucose’s values with a continuous assistance of the proposed eHealth system.","PeriodicalId":138992,"journal":{"name":"2018 IEEE 1st Colombian Conference on Applications in Computational Intelligence (ColCACI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Continuous Surveillance By Tele-consults Based on Monte Carlo Algorithms to Anticipate and Lessen Risk Levels Due to Type-2 Diabetes Complications\",\"authors\":\"H. Nieto-Chaupis\",\"doi\":\"10.1109/COLCACI.2018.8484853\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a computer-based eHealth system expected to provide tele-consults aimed to reduce complications due to the diabetes disease in adult population mainly between 30 and 60 years old. The software of the tele-consultations system which is essentially based in probabilities and entirely based in the Monte Carlo technology whose main philosophy: accept or reject, This stochastic computing method is supported with a mathematical model which is build through acquired data and experience that allows us to model and carry out predictions on the glucose’s values in time within a certain statistical error. The idea behind of this eHealth system is the rapid identification of those people with a potential risk to acquire complications derived from the high values of glucose in time. The conclusion derived from this computer-based study is that of the opportune intervention derived from the tele-consultations might alleviate and to improve the diabetes treatment by employing simple mobile phones and minimal software applications. We illustrated the prospective implementation of this tele-care system with simulations for people with an old diagnosis of diabetes and demonstrating the prospective role o these eHealth systems aimed to improve the quality of life in the middle and long term. From a combined sample 3 from 4 diabetes patients might be keeping under control their glucose’s values with a continuous assistance of the proposed eHealth system.\",\"PeriodicalId\":138992,\"journal\":{\"name\":\"2018 IEEE 1st Colombian Conference on Applications in Computational Intelligence (ColCACI)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 1st Colombian Conference on Applications in Computational Intelligence (ColCACI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COLCACI.2018.8484853\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 1st Colombian Conference on Applications in Computational Intelligence (ColCACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COLCACI.2018.8484853","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Continuous Surveillance By Tele-consults Based on Monte Carlo Algorithms to Anticipate and Lessen Risk Levels Due to Type-2 Diabetes Complications
We present a computer-based eHealth system expected to provide tele-consults aimed to reduce complications due to the diabetes disease in adult population mainly between 30 and 60 years old. The software of the tele-consultations system which is essentially based in probabilities and entirely based in the Monte Carlo technology whose main philosophy: accept or reject, This stochastic computing method is supported with a mathematical model which is build through acquired data and experience that allows us to model and carry out predictions on the glucose’s values in time within a certain statistical error. The idea behind of this eHealth system is the rapid identification of those people with a potential risk to acquire complications derived from the high values of glucose in time. The conclusion derived from this computer-based study is that of the opportune intervention derived from the tele-consultations might alleviate and to improve the diabetes treatment by employing simple mobile phones and minimal software applications. We illustrated the prospective implementation of this tele-care system with simulations for people with an old diagnosis of diabetes and demonstrating the prospective role o these eHealth systems aimed to improve the quality of life in the middle and long term. From a combined sample 3 from 4 diabetes patients might be keeping under control their glucose’s values with a continuous assistance of the proposed eHealth system.