{"title":"餐后血糖传感器数据分割分析了解血糖(GH-Method:数学-物理医学)","authors":"","doi":"10.47485/2693-2458/1014","DOIUrl":null,"url":null,"abstract":"In this paper, the author analyzed and interpreted a type 2 diabetes (T2D) patient’s postprandial plasma glucose (PPG) waveforms (i.e. curve sets), data, and key characteristics, with mathematical tools to study the physical behaviors of glucose in detail, utilizing his developed GH-Method: math-physical medicine approach.","PeriodicalId":424815,"journal":{"name":"Journal of Diabetes and Endocrinology Research","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Understanding glucose via postprandial plasma glucose sensor data segmentation analysis (GH-Method: math-physical medicine)\",\"authors\":\"\",\"doi\":\"10.47485/2693-2458/1014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the author analyzed and interpreted a type 2 diabetes (T2D) patient’s postprandial plasma glucose (PPG) waveforms (i.e. curve sets), data, and key characteristics, with mathematical tools to study the physical behaviors of glucose in detail, utilizing his developed GH-Method: math-physical medicine approach.\",\"PeriodicalId\":424815,\"journal\":{\"name\":\"Journal of Diabetes and Endocrinology Research\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Diabetes and Endocrinology Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47485/2693-2458/1014\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Diabetes and Endocrinology Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47485/2693-2458/1014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Understanding glucose via postprandial plasma glucose sensor data segmentation analysis (GH-Method: math-physical medicine)
In this paper, the author analyzed and interpreted a type 2 diabetes (T2D) patient’s postprandial plasma glucose (PPG) waveforms (i.e. curve sets), data, and key characteristics, with mathematical tools to study the physical behaviors of glucose in detail, utilizing his developed GH-Method: math-physical medicine approach.
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