This research introduces an affective explainable AI clinical decision support system that makes AI-driven cannabis use predictions transparent and interpretable for healthcare professionals.

• Enhances algorithm explainability to overcome the "black box" problem in healthcare AI
• Incorporates emotional intelligence factors to improve clinical decision support
• Addresses trust and adoption barriers for AI in medical applications
• Provides a framework for transparent clinical decision making

Why It Matters: As cannabis use increases, clinicians need trustworthy, explainable AI tools to make informed medical decisions while understanding how the AI reaches its conclusions—crucial for responsible implementation in healthcare settings.

AXAI-CDSS: An Affective Explainable AI-Driven Clinical Decision Support System for Cannabis Use