This research demonstrates how structured output formats significantly improve LLMs' performance on complex medical questions without requiring domain-specific fine-tuning.

• Reduces dangerous hallucinations in medical responses
• Improves comprehensiveness by guiding models to cover critical aspects
• Achieves expert-level performance comparable to board-certified physicians
• Works across various commercial and open-source LLMs

Why it matters: Medical AI assistants need both accuracy and reliability to be useful in healthcare settings. This approach provides a practical method to enhance existing models without extensive retraining, potentially accelerating safe AI adoption in clinical settings.

Structured Outputs Enable General-Purpose LLMs to be Medical Experts