Prediction of metabolically healthy obesity based on dietary nutrients: a comparative analysis of six machine learning models with SHAP and LIME interpretation

Key Points

• The research aims to predict metabolically healthy obesity based on dietary nutrients using machine learning models.
• Comparative analysis of six machine learning models
• Utilization of SHAP and LIME for model interpretation
• Cohort or case-control study design
• Identified key dietary nutrients influencing metabolic health
• Different models showed varying prediction accuracy
• SHAP and LIME provided insights into model decision-making