Uncovering key factors in weight loss effectiveness through machine learning

• Published in: International Journal of Obesity Vol. 49; no. 6; pp. 1189 - 1199
• Main Authors: Yang, Hui-Wen, De la Peña-Armada, Rocío, Sun, Haoqi, Peng, Yu-Qi, Lo, Men-Tzung, Scheer, Frank A. J. L., Hu, Kun, Garaulet, Marta
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 01.06.2025
• Subjects: Adult; Body Mass Index; Body weight; Body weight loss; Boosting Machine Learning Algorithms; Cognitive Behavioral Therapy - methods; Diet; Dietary intake; Eating; Eating behavior; Effectiveness; Exercise; Female; Food intake; Humans; Learning algorithms; Machine Learning; Male; Middle Aged; Monitoring; Motivation; Obesity - psychology; Obesity - therapy; Physical activity; Treatment Outcome; Weight control; Weight loss; Weight Loss - physiology; Weight Reduction Programs

One of the main challenges in weight loss is the dramatic interindividual variability in response to treatment. We aim to systematically identify factors relevant to weight loss effectiveness using machine learning (ML). We studied 1810 participants in the ONTIME program, which is based on cognitive...