diabetes-congress-2019-keynote

2 / 7

June 24-25, 2019 | Philadelphia, USA
DIABETES, ENDOCRINOLOGY, NUTRITION
AND NURSING MANAGEMENT
2nd International Conference on
Diabetes Congress 2019 Journal of Diabetology | Volume 3
Page 7
OF EXCELLENCE
IN INTERNATIONAL
MEETINGS
YEARS
GH-METHOD: METHODOLOGY OF
MATH-PHYSICAL MEDICINE USING DIA-
BETES RESEARCH AS AN EXAMPLE
Introduction: This paper describes the math-physical medicine ap-
proach (MPM) of medical research utilizing mathematics, physics, engi-
neering models and computer science, instead of the current biochemi-
cal medicine approach (BCM) that mainly utilizes biology and chemistry.
Methodology ofMPM: Initially, the author spent four years of self-study-
ing six chronic diseases and food nutrition to gain in-depth medical do-
main knowledge. During 2014, he defined metabolism as a nonlinear,
dynamic and organic mathematical system having 10 categories with
~500 elements. Then he applied topology concept with partial differen-
tial equation and nonlinear algebra to construct a metabolism equation.
Further he defined and calculated two variables, metabolism index and
general health status unit. During the past 8.5 years, he has collected
and processed 1.5 million data. Since 2015, he developed prediction
models, i.e. equations, for both postprandial plasma glucose (PPG) and
fasting plasma glucose (FPG). He identified 19 influential factors for PPG
and five factors for FPG. Each factor has a different contribution margin
to the glucose formation. He developed PPG model using optical phys-
ics and signal processing. Furthermore, by using both wave and energy
theories, he extended his research into the risk probability of heart at-
tack or stroke. In this risk assessment, he applied structural mechanics
concepts, including elasticity, dynamic plastic and fracture mechanics to
simulate artery rupture and applied fluid dynamics concepts to simulate
artery blockage. He further decomposed 12,000 glucose waveforms with
Gerald C Hsu has completed his PhD in Mathe-
matics and has been majored in Engineering at
MIT. He has attended different universities over
17 years and studied seven academic disciplines.
He has spent 20,000 hours in T2D research. First,
he studied six metabolic diseases and food nutri-
tion during 2010-2013, then conducted research
during 2014-2018. His approach is math-physics
and quantitative medicine based on mathe-
matics, physics, engineering modeling, signal
processing, computer science, big data analyt-
ics, statistics, machine learning and AI. His main
focus is on preventive medicine using prediction
tools. He believes that the better the prediction,
the more control you have.
Gerald C Hsu
EclaireMD Foundation, USA
BIOGRAPHY
Gerald C Hsu, J Diabetol 2019, Volume 3