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Prediction of Glucose Metabolism Disorder Risk Using a Machine Learning Algorithm: Pilot Study

Prediction of Glucose Metabolism Disorder Risk Using a Machine Learning Algorithm: Pilot Study

Fujibayashi et al [7] used Hb A1c values, FPG levels, and 2-hour PG to predict instances of high future risk of developing diabetes. Complete data, including 1-hour and 2-hour PG and IRI values obtained by OGTT, may improve the prediction accuracy for diabetes risk. Previously, logistic regression (LR) analyses were used as initial screening tests [5,8-10].

Katsutoshi Maeta, Yu Nishiyama, Kazutoshi Fujibayashi, Toshiaki Gunji, Noriko Sasabe, Kimiko Iijima, Toshio Naito

JMIR Diabetes 2018;3(4):e10212

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