Prediction of individual weight loss using supervised learning: findings from the CALERIE 2 study.

Journal: The American journal of clinical nutrition
PMID: 39270937

Abstract

BACKGROUND: Predicting individual weight loss (WL) responses to lifestyle interventions is challenging but might help practitioners and clinicians select the most promising approach for each individual.

Authors

  • Christina Glasbrenner
    TUM School of Medicine and Health, Department of Health and Sport Sciences, Technical University of Munich, Munich, Germany.
  • Christoph Höchsmann
    TUM School of Medicine and Health, Department of Health and Sport Sciences, Technical University of Munich, Munich, Germany.
  • Carl F Pieper
    Duke University Older Americans Independence Center; Duke University School of Medicine; Duke University; Durham, NC, USA.
  • Paulina Wasserfurth
    TUM School of Medicine and Health, Department of Health and Sport Sciences, Technical University of Munich, Munich, Germany.
  • James L Dorling
    Human Nutrition, School of Medicine, Dentistry & Nursing, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom.
  • Corby K Martin
    Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA 70808, USA.
  • Leanne M Redman
    Pennington Biomedical Research Center, Baton Rouge, LA, United States.
  • Karsten Koehler
    TUM School of Medicine and Health, Department of Health and Sport Sciences, Technical University of Munich, Munich, Germany. Electronic address: karsten.koehler@tum.de.

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