Math-physical Medicine Research Articles

Glucose Control and Behavior Psychology of a T2D Patient using GH-Method: Mentality-Personality Modeling via Math-Physical Medicine (No. 306)

In this article, the author used 10-years’ worth of data of glucoses and prominent lifestyle details such as diet and exercise to address his glucose trend pattern analysis and progressive lifestyle behavior modifications. This progressive lifestyle behavior modification is closely related to behavior psychology. The research methodology used is the GH-Method: math-physical medicine (MPM) approach which has been developed by the author over the past decade. This “Progressive Behavior Modification concept is also a part of his Mentality-Personality Modeling (MPM). He addresses the quantitative linkage between diabetes physiological phenomena and behavior psychological influences of a type 2 diabetes (T2D) patient

Investigation of Two Glucose Coefficients of GH.f-Modulus and GH.p-Modulus based on the Data of Three Clinical Cases During the COVID-19 Period using linear Elastic Glucose Theory of GHMethod: Math-Physical Medicine, Part 8 (No. 360)

This article is Part 8 of the author’s linear elastic glucose behavior study which focuses on the deeper understanding of these two newly defined glucose coefficients, GH.f-modulus and GH.p-modulus. Findings have shown the sensitive relationships with health conditions such as obesity and diabetes and certain lifestyle components, e.g. carbs/sugar intake amount and post-meal walking steps. Hopefully in the near future, he will be able to develop a reasonable and applicable numerical ranges of these two glucose coefficients. He used his measured glucose data and predicted glucose models for both fasting plasma glucose (FPG) and postprandial plasma glucose (PPG) for three patients with chronic diseases over the COVID-19 quarantined period, from 3/1/2020 to 11/10/2020.

Medical Research of PPG Characteristics Using Candlestick Model from Wall Street via GH-Method: Math-Physical Medicine (No. 261a)

Medical Research of PPG Characteristics Using Candlestick Model from Wall Street via GH-Method: Math-Physical Medicine (No. 261a)

Applying the First-Order Interpolation Perturbation Method to Establish Predicted PPG Waveforms Based on Carbs/Sugar Intake Amounts via GH-Method: Math-Physical Medicine (No.154)

Applying the First-Order Interpolation Perturbation Method to Establish Predicted PPG Waveforms Based on Carbs/Sugar Intake Amounts via GH-Method: Math-Physical Medicine (No.154)

Different Glucose Levels Produced by Coffee and Decaffeinated Coffee Using GH-Method: Math-Physical Medicine (No. 277)

Different Glucose Levels Produced by Coffee and Decaffeinated Coffee Using GH-Method: Math-Physical Medicine (No. 277)

Accuracy of Predicted Glucose using both Natural Intelligence and Artificial Intelligence via GH-Method: Math-Physical Medicine (No. 320)

This paper describes the accuracy of using natural intelligence (NI) and artificial intelligence (AI) methods to predict three glucoses, fasting plasma glucose (FPG), postprandial plasma glucose (PPG), and daily average glucose, in comparison with the actual measured PPG by using the finger-piercing (Finger) method. The entire glucose database contains 7,652 glucoses (4 glucose data per day) over 1,913 days from 6/1/2015 through 8/27/2020

Cancer Prevention through Improvements on lifestyle and Metabolism using GH-Method: Math-Physical Medicine (No. 342)

This paper describes the author’s investigation into the prevention from having various cancers and his risk probability based on improvements on lifestyle and metabolism

A Manuscript Regarding Suicidal Death of Physicians Resulting from Psychological Stress in their Inner World (No. 355)

The author is a 73-year-old medical research scientist who recently read an article regarding physician health and death [1]. Inspired by the story and his own past experiences, he decided to write a special manuscript to be shared with medical doctors. This article has a different writing style compared to his previous 354 math-physical medicine research papers, based on a quantitative method to derive analysis results with high precision, aimed at helping patients

Using progressive lifestyle modifications via alternative medicine to control both body weight and glucose (GH-Method: math-physical medicine No. 309)

In this article, the author used 10-years’ worth of data of glucoses and prominent lifestyle details such as diet and exercise to address his glucose trend pattern analysis and progressive lifestyle behavior modifications. This progressive lifestyle behavior modification is closely related to behavior psychology. The research methodology used is the GH-Method: math-physical medicine (MPM) approach which has been developed by the author over the past decade. This “Progressive Behavior Modification” concept is also a part of his Mentality-Personality Modeling (MPM). He addresses the quantitative linkage between the physiological phenomena for diabetes and obesity along with the behavior psychological influences of a patient with chronic diseases. Food and exercise are important elements of alternative medicine that serve as the major influential factors in controlling glucose and weight, not medications.

Weight Control Trend Analysis and Progressive Behavior Modification of a T2D Patient Using GH-Method: Math-Physical Medicine (No. 307)

In this article, the author used 10-years’ worth of data of glucoses and prominent lifestyle details such as diet and exercise to address weight reduction trend pattern and his progressive lifestyle behavior modifications. The research methodology used is the GH-Method: math-physical medicine (MPM) approach which has been developed by the author over the past decade. This “Progressive Behavior Modification” concept is also a part of his Mentality-Personality Modeling (MPM). He addresses the quantitative linkage between obesity physiological phenomena and behavior psychological influences of an obese patient.

Weight Control Trend Analysis and Progressive Behavior Modification of a T2D Patient Using GH-Method: Math-Physical Medicine (No. 307)

In this article, the author used 10-years’ worth of data of glucoses and prominent lifestyle details such as diet and exercise to address weight reduction trend pattern and his progressive lifestyle behavior modifications. The research methodology used is the GH-Method: math-physical medicine (MPM) approach which has been developed by the author over the past decade. This “Progressive Behavior Modification” concept is also a part of his Mentality-Personality Modeling (MPM). He addresses the quantitative linkage between obesity physiological phenomena and behavior psychological influences of an obese patient.

Comparison between Home Cooked Meals and Dine-Out Meals Using both Glucose and Associated Energy via GH-Method: MathPhysical Medicine

Comparison between Home Cooked Meals and Dine-Out Meals Using both Glucose and Associated Energy via GH-Method: MathPhysical Medicine

How to Reverse Chronic Disease Induced Heart Conditions using a Simple and Effective “Cook Book of Quantitative Formulas” via GH-Method: Math-Physical Medicine (No. 256)

How to Reverse Chronic Disease Induced Heart Conditions using a Simple and Effective “Cook Book of Quantitative Formulas” via GH-Method: Math-Physical Medicine (No. 256)

A Biophysical Study of Relationships Among Nutrition, Glucose, and Neuroscience via Ppg Waveform Differences between Liquid Egg Meals and Solid Egg Meals Using Gh-Method: Math-Physical Medicine (No.294)

In this paper, the author describes his 2+ years (801 days) research results, from 5/5/2018 through 7/14/2020, using his 171 special meals glucose data. Initially, he researched the detailed postprandial plasma glucose (PPG) data resulting from both food intake and post-meal exercise via 97 solid egg meals (74 pan-fried and 23 hard broiled) and 74 liquid egg meals (egg drop soup). Based on his findings, he adopted a statistical method of “decision making via elimination” to search and verify a hypothetical neural communication model between the brain’s cerebral cortex and internal organs, such as the stomach, intestines, liver, and pancreas

Diabetes Control and Metabolism Maintenance During Covid-19 Period in Comparison to Three Other Periods Using GH-Method: Math-Physical Medicine

This paper describes the author’s quantitative results of diabetes control and metabolism maintenance within a 4.5-year period covering two years from 7/1/2018 to 6/30/2020. Special attention has been placed on the COVID-19 quarantine period from 1/1/2020 to 6/30/2020. COVID-19 is more than 100 times worse than SARS that occurred in 2003, in terms of its spreading speed, fatality number, and emotional impact on the world population. People belonging to the “vulnerable” groups, such as the elderly with existing chronic diseases and history of complications, or people with psychological disorders, who require special attention to their health conditions and lifestyle management during this quarantine period. However, during this time, the author has achieved better results on both of his diabetes control and metabolism management. The knowledge and experience he has acquired in the past 10 years of medical research and his developed MI model and diabetes prediction tools have assisted him in many ways. As a result, he has turned the COVID-19 crisis into his health advantage!

HbA1C Conversion Using the ADA Formula of eAG in Comparison with the eclaireMD Mathematically Developed A1C Model Results via GH-Method: Math-Physical Medicine (No. 155)

HbA1C Conversion Using the ADA Formula of eAG in Comparison with the eclaireMD Mathematically Developed A1C Model Results via GH-Method: Math-Physical Medicine (No. 155)

Cancer Prevention Through Improvements on Lifestyle and Metabolism Using GH-Method: Math-Physical Medicine (No. 342)

This paper describes the author’s investigation into the prevention from having various cancers and his risk probability based on improvements on lifestyle and metabolism. His risk probabilities percentage of having cancer over the past 11 years with lower risk percentages (<50%) from 2014 - 2020 and higher risk percentages (>50%) from 2010 - 2013. It should be noted that the higher prediction accuracy occurred during 2015-2020 due to his collection of more completed data. (1) Year of 2010: 88% (2) Year of 2011: 74% (3) Year of 2012: 58% (4) Year of 2013: 55% (5) Year of 2014: 50% (6) Year of 2015: 48% (7) Year of 2016: 46% (8) Year of 2017: 45% (9) Year of 2018: 45% (10)Year of 2019: 45% (11)Year of 2020: 43% It seems that 50% is a reasonable “cut-off ” line between higher risk versus lower risk. The trend of the past 11 years risk probability percentages of having cancer from the viewpoint of cancer prevention is being reduced year after year, which is an encouraging fact. The calculated cancer prevention and risk probability results via lifestyle and metabolism have been validated by his many health examination reports from the past 20 years. This big data based on a dynamic simulation model and data mining using GH-Method: math-physical medicine approach can provide an early warning to which factors or areas to monitor in order to continuously improve his health conditions. The author wrote this article to share with other people, who may have similar interest in reducing their risk probability of getting cancer. As stated previously, he is not an expert on oncology but a research scientist in both lifestyle and metabolism. Metabolism and cancer have a strong relationship with one another; therefore, hopefully, his research method and preliminary findings would have some merit to help others to prevent them from getting cancer.

Investigating the Influential Factors on Body Weight and Its Impact on Glucoses Using GH-Method: Math-Physical Medicine (No. 327)

The author attempts to identify three major and two secondary influential factors of body weight along with its impact on six different glucose components using Pearson correlation coefficient “R” of statistics to calculate different degree of association between two datasets. This investigation utilized the daily weight and glucose data in conjunction with six lifestyle details, including food, exercise, water, sleep, and weather temperature, during a period of ~6 years from 1/1/2015 to 9/11/2020

Lifestyle Medicine Practice to Diagnose the Relationship between Sleep Patterns and Glucoses of Three Type 2 Diabetes Patients Using GH-Method: Math-Physical Medicine (No. 353)

The author applies his GH-method: math-physical medicine research methodology and lifestyle medicine practice to diagnose the relationship between sleep patterns and glucoses of three type 2 diabetes (T2D) patients in particular the female case referred to as Case A, who has an irregular sleep pattern

Self-Recovery of Pancreatic Beta Cell’s Insulin Secretion Based on 10+ Years Annualized Data of Food, Exercise, Weight, and Glucose Using GH-Method: Math-Physical Medicine (No. 339)

The author was inspired from reading two recently published medical papers regarding pancreatic beta cells insulin secretion or diabetes reversal via weight reduction. The weight reduction is directly related to the patient’s lifestyle improvement through diet and exercise. He has published six medical papers on beta cells based on different stages in observations of his continuous glucose improvements; therefore, in this article, he will investigate food ingredients, meal portions, weight, and glucose improvement based on his 10+ years of collected big data