Using Topology Concept of Mathematics and Finite Element Method of Engineering to Develop a Mathematical Model of Metabolism in medicine in order to Control Various Chronic Diseases and their Complications via Overall Health Conditions Improvement Based on GH-Method: Math-Physical Medicine (No. 453)

Abstract

Gerald C Hsu

The author spent 11 years with more than 30,000 hours to self-study and research chronic diseases and lifestyle details in order to control his severe type 2 diabetes (T2D) and various diabetic complications. After self-studying endocrinology and food nutrition for 4 years, from 2010 to 2013, he applied the learned medicine and food knowledge combined with his background of four academic disciplines and practical experiences on mathematics, physics, engineering, and computer science (big data analytics and artificial intelligence) to develop a mathematical model of metabolism during the entire year of 2014. He continued with his development effort of several prediction tools for weight, fasting plasma glucose (FPG), postprandial plasma glucose (PPG), daily glucose, and HbA1C in 2015-2016. Starting from 2017, he started to write papers based on his findings from his research and then published them in various journals. This particular metabolism model includes 10 major categories: 4 medical conditions including weight (M1), glucose (M2), blood pressure (M3), lipids (M4); with 6 lifestyle details including exercise (M5), water intake (M6), sleep (M7), stress (M8), food and meal (M9), and life routines regularity (M10). These 10 categories contain approximately 500 input and output elements. For example, he spent 9 months on developing the stress category with 34 elements. The total number of data collected and processed during the past 10 years have already exceeded 2 million. During 2015 to 2021, for a period of 6.5 years, he applied many theories and techniques from mathematics, physics, and engineering into his medical research work. This included topology, nonlinear algebra, finite element method, linear elastic theory, wave theory, energy theory, quantum mechanics, optical physics, statistics, machine learning, big data analytics, and artificial intelligence (AI). These various theories and techniques have effectively served as his research tools in order to complete many of the medical research tasks. As a result, his collected personal data of both biomarkers and lifestyle details were utilized to illustrate the development process of building a metabolism model of medicine using topology concept of mathematics, finite element method of engineering along with other applicable theories and principles of physics (applied math) and engineering (applied physics). This paper describes the author’s selected approach of building a mathematical model of metabolism. It uses the topology concept, part of finite element engineering modeling technique, applicable theories and principles from physics and engineering, such as optical physics, energy theory, wave theory, linear elasticity, perturbation theory of quantum mechanics, and various computer science and AI tools to investigate and develop a rather complicated metabolism model in a highly quantitative manner. Optimistically and pleasantly, it has actually achieved certain high prediction accuracy in results based on a simple concept but rather general scope of “Metabolism”.

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