Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69220, first published .
Development of Machine Learning–Based Risk Prediction Models to Predict Rapid Weight Gain in Infants: Analysis of Seven Cohorts

Development of Machine Learning–Based Risk Prediction Models to Predict Rapid Weight Gain in Infants: Analysis of Seven Cohorts

Development of Machine Learning–Based Risk Prediction Models to Predict Rapid Weight Gain in Infants: Analysis of Seven Cohorts

Miaobing Zheng   1, 2 , PhD ;   Yuxin Zhang   1 , PhD ;   Rachel A Laws   1 , PhD ;   Peter Vuillermin   3 , PhD ;   Jodie Dodd   4 , PhD ;   Li Ming Wen   5 , PhD ;   Louise A Baur   5 , PhD ;   Rachael Taylor   6 , PhD ;   Rebecca Byrne   7 , PhD ;   Anne-Louise Ponsonby   8 , PhD ;   Kylie D Hesketh   1 , PhD

1 Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia

2 School of Health Sciences, Faculty of Health & Medicine, UNSW Sydney, Kensington, Australia

3 Barwon Health, Geelong, Australia

4 Discipline of Obstetrics and Gynaecology, The Robinson Research Institute, The University of Adelaide, Adelaide, Australia

5 School of Public Health and Sydney Medical School, The University of Sydney, Sydney, Australia

6 Department of Medicine, University of Otago, Dunedin, New Zealand

7 School of Exercise and Nutrition Sciences, Faculty of Health, Queensland University of Technology, Kelvin Grove, Australia

8 The Florey Institute of Neuroscience and Mental Health, Murdoch Children's Research Institute, Royal Children's Hospital, The University of Melbourne, Parkville, Australia

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