Practical guide to SHAP analysis: Explaining supervised machine learning model predictions in drug development

Practical guide to SHAP analysis: Explaining supervised machine learning model predictions in drug development Despite increasing interest in using Artificial Intelligence (AI) and Machine Learning (ML) models for drug development, effectively interpreting their predictions remains a challenge, which limits their impact on clinical decisions. We address this issue by providing a practical guide to SHapley Additive exPlanations (SHAP), a popular feature-based interpretability method, which can b...