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Cancer Congress 2019
Journal of Cancer Immunology &Therapy | Volume 2
Page 14
July 22-23, 2019 | Brussels, Belgium
OF EXCELLENCE
IN INTERNATIONAL
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CANCER SCIENCE AND THERAPY
2
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Fourier Transform to conduct frequency domain analyses to discover some hidden characteristics of glucose waves. Then he
developed an AI Glucometer tool for patients to predict their weight, FPG, PPG and A1C. It uses various computer science
tools, including big data analytics, machine learning (self-learning, correction and simplification) and artificial intelligence to
achieve very high accuracy (95% to 99%).
Results:
In 2010, his average glucose was 280mg/dL and A1C was >10%. Now, his glucose value is 116mg/dL and A1C is 6.5%.
Since his health condition is stable, no longer he suffers from repetitive cardiovascular episodes.
Conclusion:
Instead of utilizing traditional biology, chemistry and statistics, the methodology of GH-Method: math-physical
medicineuses advancedmathematics, physics concept, engineeringmodellingand computer science tools (Bigdata analytics,
artificial intelligence) which can be applied to other branches of medical research in order to achieve a higher precision and
deeper insight.