This research evaluates how well large language models can handle complex medical cases and provide explanations that could meaningfully support clinical decision-making.

• Tests LLMs against realistic clinical cases beyond standard medical licensing exams
• Assesses both answer accuracy and the quality of explanations provided
• Reveals current capabilities and limitations of AI in complex medical reasoning
• Creates benchmarks to drive improvement in medical AI applications

This research matters because effective clinical support tools require not just correct answers but also sound reasoning that doctors can trust and validate before making critical decisions.

Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questions