Published on in Vol 7 , No 3 (2022) :Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32366, first published .
Machine Learning–Derived Prenatal Predictive Risk Model to Guide Intervention and Prevent the Progression of Gestational Diabetes Mellitus to Type 2 Diabetes: Prediction Model Development Study

Machine Learning–Derived Prenatal Predictive Risk Model to Guide Intervention and Prevent the Progression of Gestational Diabetes Mellitus to Type 2 Diabetes: Prediction Model Development Study

Machine Learning–Derived Prenatal Predictive Risk Model to Guide Intervention and Prevent the Progression of Gestational Diabetes Mellitus to Type 2 Diabetes: Prediction Model Development Study

Mukkesh Kumar 1, 2, 3 , BEng (Hons I) ;   Li Ting Ang 1, 2 , BSc ;   Cindy Ho 1, 2 , BSc ;   Shu E Soh 4 , PhD ;   Kok Hian Tan 5, 6 , MBBS, MMed, MBA ;   Jerry Kok Yen Chan 7, 8, 9 , MB BCh BaO (Hons), PhD ;   Keith M Godfrey 10, 11 , BM in Medicine (Honours & Clinical Distinction), PhD ;   Shiao-Yng Chan 1, 7 , MBBS, PhD ;   Yap Seng Chong 1, 7 , MBBS, MMeD, MD ;   Johan G Eriksson 1, 7, 12, 13 * , MD, DMSc ;   Mengling Feng 3, 14 * , PhD ;   Neerja Karnani 1, 2, 15 * , PhD

1 Singapore Institute for Clinical Sciences , Agency for Science Technology and Research , Singapore , SG

2 Bioinformatics Institute , Agency for Science Technology and Research , Singapore , SG

3 Saw Swee Hock School of Public Health , National University of Singapore , National University Health System , Singapore , SG

4 Department of Paediatrics , Yong Loo Lin School of Medicine , National University of Singapore , Singapore , SG

5 Division of Obstetrics and Gynecology , KK Women’s and Children’s Hospital , Singapore , SG

6 Obstetrics and Gynecology Academic Clinical Programme , Duke-NUS Graduate Medical School , Singapore , SG

7 Department of Obstetrics and Gynaecology and Human Potential Translational Research Programme , Yong Loo Lin School of Medicine , National University of Singapore , Singapore , SG

8 Department of Reproductive Medicine , KK Women’s and Children’s Hospital , Singapore , SG

9 Cancer and Stem Cell Biology , Duke-NUS Medical School , Singapore , SG

10 MRC Lifecourse Epidemiology Unit , University of Southampton , Southampton , GB

11 National Institute for Health and Care Research Southampton Biomedical Research Centre , University Hospital Southampton NHS Foundation Trust , Southampton , GB

12 Department of General Practice and Primary Health Care , University of Helsinki , Helsinki , FI

13 Folkhälsan Research Center , Helsinki , FI

14 Institute of Data Science , National University of Singapore , Singapore , SG

15 Department of Biochemistry , Yong Loo Lin School of Medicine , National University of Singapore , Singapore , SG

*these authors contributed equally

Corresponding Author:

  • Neerja Karnani, PhD
  • Singapore Institute for Clinical Sciences
  • Agency for Science Technology and Research
  • Brenner Centre for Molecular Medicine
  • 30 Medical Drive
  • Singapore
  • SG
  • Phone: 65 64074041
  • Email: neerja_karnani@sics.a-star.edu.sg