Predicting Weight Loss Success After Gastric Sleeve Surgery: A Machine Learning-Based Approach.

Journal: Nutrients
PMID: 40284254

Abstract

BACKGROUND/OBJECTIVES: Obesity is a global health issue, and in this context, bariatric surgery is considered the most effective treatment for severe cases. However, postoperative outcomes vary widely among individuals, driving the development of tools to predict body weight loss success. The main objective of this paper is to evaluate predictive variables for successful weight loss one year after Sleeve bariatric surgery, defining success as a weight loss exceeding 30%.

Authors

  • Mónica Casas Domínguez
    Department of Signal Theory and Communications, and Telematics Engineering, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain.
  • Isabel Herrena Montano
    Department of Signal Theory and Communications, and Telematics Engineering, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain.
  • Juan Jose López Gómez
    Investigation Centre Endocrinology and Nutrition, Faculty of Medicine, University of Valladolid, 47003 Valladolid, Spain.
  • Beatriz Ramos Bachiller
    Research Center for Endocrinology and Clinical Nutrition, University of Valladolid, 47003 Valladolid, Spain.
  • Daniel Antonio de Luis Román
    Research Center for Endocrinology and Clinical Nutrition, University of Valladolid, 47003 Valladolid, Spain.
  • Isabel de la Torre Diez
    Department of Signal Theory and Communications and Telematic Engineering, University of Valladolid, Paseo de Belén 15, 47011 Valladolid, Spain.

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