Using Math-Physics Medicine to Analyze Metabolism & Improve Health Conditions
The author spent seven years and 18,000 hours to study, analyze and research his chronic disease conditions.
Here is the comparison between 2010 and 2017:
Weight: 205 / 172 lbs.
Waistline: 44 / 34 inches
PPG: 350 / 116 mg/dL
FPG: 185 / 119 mg/dL
Daily glucose: 280 / 117 mg/dL
A1C: 10.0 / 6.1 %
ACR: 116 / 12 mg/mmol
Triglycerides: 1161 / 69 mg/dL
He used mathematics, physics, engineering modeling, and computer science (big data analytics and artificial intelligence) to derive the mathematical metabolism model and three prediction tools for weight, fasting plasma glucose (FPG), and postprandial glucose (PPG) with >30 input elements. This study includes 11 categories: weight, glucose, blood pressure, lipids, food, water, exercise, sleep, stress, life pattern regularity, time, with ~500 input and output elements. He collected more than 1 million “clean” data over 7 years.
He defined two new terms known as the Metabolism Index (MI) and General Health Status Unit (GHSU). The “health state” is expressed as the “break-even” line which is 73.5%; above this percentage is regarded “unhealthy” and below the break-even line is “healthy”. The results showed that he was very unhealthy (80%-110%) before 2013. The curve went through a sharp decline in 2014 due to his research. After 2015, he was “healthy” (60%-70%). As of 12/21/2017, his MI is 55.3% and GHSU is 56.1%. All of his previous lab test results confirmed with the diagram showing his chronic disease conditions are well under control.