{"title":"基于移动的妊娠糖尿病决策支持系统","authors":"E. Pustozerov, P. Popova","doi":"10.1109/USBEREIT.2018.8384546","DOIUrl":null,"url":null,"abstract":"The paper presents a gestational diabetes mellitus monitoring system with implemented information support modules for physicians and patients. The system provides an infrastructure for physician-patient remote interaction in-between hospital visits with implemented structuring and analysis of data on blood glucose, diet, insulin injections, physical activity, patient's individual characteristics and data derived from laboratory tests. These data are used to provide two types of recommendations: autonomous on-the-point individualized advice on the diet, generated by the prognostic blood glucose models, and physician's decision making recommendations, based on the data extracted from patients' electronic diaries and signals.","PeriodicalId":176222,"journal":{"name":"2018 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Mobile-based decision support system for gestational diabetes mellitus\",\"authors\":\"E. Pustozerov, P. Popova\",\"doi\":\"10.1109/USBEREIT.2018.8384546\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a gestational diabetes mellitus monitoring system with implemented information support modules for physicians and patients. The system provides an infrastructure for physician-patient remote interaction in-between hospital visits with implemented structuring and analysis of data on blood glucose, diet, insulin injections, physical activity, patient's individual characteristics and data derived from laboratory tests. These data are used to provide two types of recommendations: autonomous on-the-point individualized advice on the diet, generated by the prognostic blood glucose models, and physician's decision making recommendations, based on the data extracted from patients' electronic diaries and signals.\",\"PeriodicalId\":176222,\"journal\":{\"name\":\"2018 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/USBEREIT.2018.8384546\",\"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 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/USBEREIT.2018.8384546","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mobile-based decision support system for gestational diabetes mellitus
The paper presents a gestational diabetes mellitus monitoring system with implemented information support modules for physicians and patients. The system provides an infrastructure for physician-patient remote interaction in-between hospital visits with implemented structuring and analysis of data on blood glucose, diet, insulin injections, physical activity, patient's individual characteristics and data derived from laboratory tests. These data are used to provide two types of recommendations: autonomous on-the-point individualized advice on the diet, generated by the prognostic blood glucose models, and physician's decision making recommendations, based on the data extracted from patients' electronic diaries and signals.