Risk Probability of Having a Cardiovascular Disease, Stroke, or Renal Complications Using Annual Segmented Data of Glucose and Metabolism Index (GH Method: Math-Physical Medicine)

Abstract

Method In 2014, the author applied topology concept, finite-element engineering technique, and nonlinear algebra operations to develop a mathematical metabolism model, which contains ten categories including four output categories (weight, glucose, BP, other labtested data including lipids & ACR) and six input categories (food, water drinking, exercise, sleep, stress, routine life patterns and safety measures). These 10 metabolic categories include approximately 500 detailed elements. He further defined a new parameter referred to as the metabolism index (MI) that has a combined score of the above metabolic categories and elements. Since 2012, he has collected and stored ~2 million data from his own body health conditions and personal lifestyle details.