Work

Leveraging Machine Learning and Ecological Momentary Assessment Data to Identify Factors That Predict Children's Energy Intake

Year: 2026

Type: article

Abstract: Objectives: Ecological Momentary Assessment (EMA) studies show near-real-time physical, social, and contextual factors are associated with changes in children’s dietary intake. Because machine learning (ML) can utilize high-dimensional data, this study leverages EMA and ML to identify the dynamic predictors of children’s energy intake (EI).

Source: Current Developments in Nutrition

DOI: 10.1016/j.cdnut.2026.107838