I (Yuhan Du) am proud to present my poster entitled “Prediction of Gestational Diabetes Mellitus in Overweight and Obese Caucasian Women using Machine Learning” coauthored by Professor Fionnuala M McAuliffe and Dr Catherine Mooney at AMIA Informatics Summit 2021 on March 23, 2021.
The poster presents our initial results on predicting gestational diabetes mellitus (GDM) in overweight and obese Caucasian pregnant women. GDM is a common pregnancy complication associated with many maternal and neonatal consequences, and it is increased in risk by overweight and obesity. We applied machine learning to develop prediction models for GDM in overweight and obese Caucasian women to identify at-risk women in need of intervention early in pregnancy. This work was based on maternal characteristics and blood biomarkers at baseline from the PEARS study. After appropriate data preparation and feature selection, five machine learning algorithms were applied with synthetic minority oversampling technique and five-fold cross validation repeated five times optimising the area under precision-recall curve. Our results showed that a support vector machine with polynomial kernel outperformed other algorithms, identifying 44% and 67% of GDM women in early pregnancy at 5% and 10% false positive rate respectively. This work demonstrates the potential of applying machine learning to the prediction of GDM in a clinical setting.
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–Yuhan