{"title":"糖尿病患者低血糖预测移动软件设计研究","authors":"Miyeon Jung","doi":"10.1145/2897073.2897129","DOIUrl":null,"url":null,"abstract":"To alert diabetes patients of incipient hypoglycemia, we developed a hypoglycemia prediction algorithm and elicited design inspiration for new glucose management software. To identify the predictive factors, we conducted surveys, interviews, and diary studies, and developed a prediction model that uses self-monitored blood glucose. We tested the accuracy of prediction algorithms achieved by different machine learning methods, and found that the proposed algorithms have potential to predict hypoglycemia. Based on the proposed algorithm, we designed a new mobile application concept to support patients’ self-care, especially to avert hypoglycemia.","PeriodicalId":296509,"journal":{"name":"2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Toward Designing Mobile Software to Predict Hypoglycemia for Patients with Diabetes\",\"authors\":\"Miyeon Jung\",\"doi\":\"10.1145/2897073.2897129\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To alert diabetes patients of incipient hypoglycemia, we developed a hypoglycemia prediction algorithm and elicited design inspiration for new glucose management software. To identify the predictive factors, we conducted surveys, interviews, and diary studies, and developed a prediction model that uses self-monitored blood glucose. We tested the accuracy of prediction algorithms achieved by different machine learning methods, and found that the proposed algorithms have potential to predict hypoglycemia. Based on the proposed algorithm, we designed a new mobile application concept to support patients’ self-care, especially to avert hypoglycemia.\",\"PeriodicalId\":296509,\"journal\":{\"name\":\"2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2897073.2897129\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2897073.2897129","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Toward Designing Mobile Software to Predict Hypoglycemia for Patients with Diabetes
To alert diabetes patients of incipient hypoglycemia, we developed a hypoglycemia prediction algorithm and elicited design inspiration for new glucose management software. To identify the predictive factors, we conducted surveys, interviews, and diary studies, and developed a prediction model that uses self-monitored blood glucose. We tested the accuracy of prediction algorithms achieved by different machine learning methods, and found that the proposed algorithms have potential to predict hypoglycemia. Based on the proposed algorithm, we designed a new mobile application concept to support patients’ self-care, especially to avert hypoglycemia.