Open AccessUsing GH-Method: Math-Physical Medicine to Conduct Segmentation Analysis to Investigate the Impact of Weather Temperatures on Glucose (Both FPG And PPG)
Publication year - 2020
Publication title -
medical and clinical research
Language(s) - English
Resource type - Journals
ISSN - 2577-8005
DOI - 10.33140/mcr.05.03.02
Subject(s) - postprandial , plasma glucose , segmentation , big data , diabetes mellitus , medicine , zoology , mathematics , endocrinology , atmospheric sciences , computer science , artificial intelligence , physics , data mining , biology
This paper is based on big data collected from a period of1,420daysfrom 6/1/2015 to 4/21/2019 with a total of 4,260 data,including highest ambient temperature (weather) of each dayin degree Fahrenheit (°F), fasting plasma glucose (FPG) andpostprandial plasma glucose (PPG) in mg/dL. The dataset is providedby the author, who uses his own type 2 diabetes metabolic conditionscontrol, as a case study via the “math-physical medicine” approachof a non-traditional methodology in medical research.