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

Authors

  • Gerald C. Hsu eclaireMD Foundation, USA Author

DOI:

https://doi.org/10.47363/JDRR/2021(3)144

Keywords:

Natural Intelligence , Artificial Intelligence, GH-Method, Math-Physical Medicine

Abstract

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. 

Author Biography

  • Gerald C. Hsu, eclaireMD Foundation, USA

    eclaireMD Foundation, USA 

Downloads

Published

2020-12-30