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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

Journals

  1. Huang L, Chen J. Interpretable machine learning for identifying adolescent obesity risk and identifying key determinants. Frontiers in Public Health 2026;14 View
  2. Shinoda G, Ishikuro M, Matsubara T, Noda A, Murakami K, Orui M, Metoki H, Kikuya M, Hozawa A, Kuriyama S, Nakamura K, Obara T. Routine Life-Course Health Records in Infancy Predict Being Overweight in Childhood and Adolescence: The TMM BirThree Cohort Study. Children 2026;13(3):334 View
  3. Ortega-Ramírez A, Sánchez-Ramírez C, Trujillo-Hernández B, Murillo Zamora E. Predicting rapid weight gain in six-month-old infants: an exploratory modeling study. Pediatric Research 2026 View