Development and validation of an explainable machine learning-based risk prediction model for obesity in Chinese children and adolescents: a population-based st... (opens in new tab)

BackgroundChildhood obesity represents a significant global public health challenge. Accurate and rapid prediction models for identifying obesity risk in children and adolescents are essential for facilitating early prevention and enabling timely interventions. However, interpretable and user-friendly obesity risk prediction models based on nationally representative data remain limited. This study aimed to develop and validate a model to predict current obesity risk among children and adolesc...