{"title":"碳水化合物估算误差对1型糖尿病血糖控制的影响","authors":"Qingnan Sun, Marko V. Jankovic, S. Mougiakakou","doi":"10.1109/NEUREL.2018.8586983","DOIUrl":null,"url":null,"abstract":"This article investigates the impact of carbohydrate (CHO) estimation error on three different algorithms for insulin treatment optimisation. The experiments were conducted using the educational version of the UVa/Padova simulator on 11 virtual adult subjects. Under different CHO estimation error levels, two ways of CHO amount announcements were investigated: numerical value and categorical value (Small, Medium, and Large). Results of experiments suggest that by low CHO estimation error, the way of CHO level announcement has low impact on algorithm quality. As the error increases more intelligent algorithmic approaches need to be investigated.","PeriodicalId":371831,"journal":{"name":"2018 14th Symposium on Neural Networks and Applications (NEUREL)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Impact of Errors in Carbohydrate Estimation on Control of Blood Glucose in Type 1 Diabetes\",\"authors\":\"Qingnan Sun, Marko V. Jankovic, S. Mougiakakou\",\"doi\":\"10.1109/NEUREL.2018.8586983\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article investigates the impact of carbohydrate (CHO) estimation error on three different algorithms for insulin treatment optimisation. The experiments were conducted using the educational version of the UVa/Padova simulator on 11 virtual adult subjects. Under different CHO estimation error levels, two ways of CHO amount announcements were investigated: numerical value and categorical value (Small, Medium, and Large). Results of experiments suggest that by low CHO estimation error, the way of CHO level announcement has low impact on algorithm quality. As the error increases more intelligent algorithmic approaches need to be investigated.\",\"PeriodicalId\":371831,\"journal\":{\"name\":\"2018 14th Symposium on Neural Networks and Applications (NEUREL)\",\"volume\":\"189 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 14th Symposium on Neural Networks and Applications (NEUREL)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NEUREL.2018.8586983\",\"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 14th Symposium on Neural Networks and Applications (NEUREL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NEUREL.2018.8586983","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Impact of Errors in Carbohydrate Estimation on Control of Blood Glucose in Type 1 Diabetes
This article investigates the impact of carbohydrate (CHO) estimation error on three different algorithms for insulin treatment optimisation. The experiments were conducted using the educational version of the UVa/Padova simulator on 11 virtual adult subjects. Under different CHO estimation error levels, two ways of CHO amount announcements were investigated: numerical value and categorical value (Small, Medium, and Large). Results of experiments suggest that by low CHO estimation error, the way of CHO level announcement has low impact on algorithm quality. As the error increases more intelligent algorithmic approaches need to be investigated.
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