KEDRec-LM combines large language models with medical knowledge graphs to create an explainable system for drug discovery and recommendation.

• Utilizes open-source drug knowledge graphs, clinical trial data, and PubMed publications
• Delivers explainable drug recommendations that help clinicians understand the reasoning behind suggestions
• Applies knowledge distillation techniques to improve model performance and efficiency
• Bridges the gap between AI capabilities and practical medical applications

This research matters because it enhances drug discovery processes with transparent AI reasoning, potentially accelerating treatment development while maintaining clinical trust through explainability.

KEDRec-LM: A Knowledge-distilled Explainable Drug Recommendation Large Language Model