{"title":"从公共卫生角度探讨营养和运动对肥胖、糖尿病和心血管风险的控制(GH-Method:数学-物理医学)","authors":"Gerald C. Hsu","doi":"10.47363/jcrrr/2020(1)109","DOIUrl":null,"url":null,"abstract":"Methods The author spent 23,000 hours during the past 8.5 years using math-physical medicine to conduct his research. He has collected and processed ~1.5 million data, including ~300,000 medical conditions, and ~1.2 million lifestyle details. He then utilized the GH-Method: math-physical medicine (MPM) which involves advanced mathematics, optical physics, signal processing, energy and wave theories, statistics, big data analytics, machine learning, artificial intelligence to develop five prediction models, including weight, FPG, PPG, adjusted glucose, and HbA1C.","PeriodicalId":430938,"journal":{"name":"Journal of Cardiology Research Review & Reports","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"From a Public Health Point of View to Investigate the Control of Obesity, Diabetes, and Cardiovascular Risk Via Nutrition and Exercise (GH-Method: Math-Physical Medicine)\",\"authors\":\"Gerald C. Hsu\",\"doi\":\"10.47363/jcrrr/2020(1)109\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Methods The author spent 23,000 hours during the past 8.5 years using math-physical medicine to conduct his research. He has collected and processed ~1.5 million data, including ~300,000 medical conditions, and ~1.2 million lifestyle details. He then utilized the GH-Method: math-physical medicine (MPM) which involves advanced mathematics, optical physics, signal processing, energy and wave theories, statistics, big data analytics, machine learning, artificial intelligence to develop five prediction models, including weight, FPG, PPG, adjusted glucose, and HbA1C.\",\"PeriodicalId\":430938,\"journal\":{\"name\":\"Journal of Cardiology Research Review & Reports\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cardiology Research Review & Reports\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47363/jcrrr/2020(1)109\",\"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 Cardiology Research Review & Reports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47363/jcrrr/2020(1)109","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
From a Public Health Point of View to Investigate the Control of Obesity, Diabetes, and Cardiovascular Risk Via Nutrition and Exercise (GH-Method: Math-Physical Medicine)
Methods The author spent 23,000 hours during the past 8.5 years using math-physical medicine to conduct his research. He has collected and processed ~1.5 million data, including ~300,000 medical conditions, and ~1.2 million lifestyle details. He then utilized the GH-Method: math-physical medicine (MPM) which involves advanced mathematics, optical physics, signal processing, energy and wave theories, statistics, big data analytics, machine learning, artificial intelligence to develop five prediction models, including weight, FPG, PPG, adjusted glucose, and HbA1C.
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