Using Time-Series and Spatial Analysis (Math-Physical Medicine) to Investigate the Relationships among Weight, Blood Pressure, Glucose, Food and Exercise
Journal: Journal of Diabetes and Endocrinology Research (Vol.2, No. 2)Publication Date: 2020-04-10
- Using Time-Series and Spatial Analysis (Math-Physical Medicine) to Investigate the Relationships among Weight, Blood Pressure, Glucose, Food and Exercise
- Using GH-Method: math-physical medicine approach and various glucose data to investigate the health state of a type 2 diabetes patient’s pancreatic β- cells
- Investigation the importance of metabolism on body weight and glucose for 8.5 years using GH-Method: math-physical medicine (No. 300)
- Understanding glucose via postprandial plasma glucose sensor data segmentation analysis (GH-Method: math-physical medicine)
- Using PPG Segmentation Analysis, Waveform Characteristics Analysis and Energy Theory to Investigate the Linkage among Brain, Liver, and Gastrointestinal System (GH-Method: Math-physical Medicine)
Abstract
The author uses his own type 2 diabetes metabolic conditions control as a case study using the “math-physical medicine” approach of a non-traditional methodology in medical research. Math-physical medicine (MPM) starts with the observation of the human body's physical phenomena (not biological or chemical characteristics), collecting elements of the disease related data (preferring big data), utilizing applicable engineering modeling techniques, developing appropriate mathematical equations (not just statistical analysis), and finally predicting the direction of the development and control mechanism of the disease.
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Last modified: 2020-11-18 17:02:59