Published on 05.07.2022 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 July 26, 2021.

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}

; Li Ting Ang^{1, 2}

; Cindy Ho^{1, 2}

; Kok Hian Tan^{5, 6}

; Jerry Kok Yen Chan^{7, 8, 9}

; Keith M Godfrey^{10, 11}

; Shiao-Yng Chan^{1, 7}

; Yap Seng Chong^{1, 7}

; Johan G Eriksson^{1, 7, 12, 13}

; Mengling Feng^{3, 14}

; Neerja Karnani^{1, 2, 15}

Article Authors Cited by (16) Tweetations (4) Metrics

Altmetric

Altmetric discovers Social Media mentions. Click the ‘See more details’ link for a full report.

Dimensions

Dimensions discovers Citations. Click the ‘details’ link for a full report.

Metrics Since Publication

Daily | Monthly | Annually