AI-Driven Explainable Medication and DDI Predictions

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This presentation explores the integration of AI in healthcare, specifically focusing on medication and drug-drug interaction (DDI) analysis. We discuss the importance of explainability in AI applications and review methods like XGBoost, SHAP, and Graph Neural Networks to enhance interpretability and precision. Insights include achieving high accuracy, building clinical trust, and implications for pharmacy analytics. Future directions highlight real-world validation, advanced multi-label...