Multi-Agent Reasoning with Consistency Verification Improves Uncertainty Calibration in Medical MCQA

1. 1Implement a multi-agent framework with domain-specific specialist agents
2. 2Use Two-Phase Verification to ensure consistency across agents
3. 3Apply S-Score Weighted Fusion to combine agent outputs
4. 4Evaluate and refine the model using medical multiple-choice question answering datasets

AI engineers and researchers working on medical AI applications can benefit from this approach to improve model calibration and reliability, while data scientists and clinicians can use the results to make more informed decisions

💡 Combining specialist agents with consistency verification and weighted fusion can improve model calibration and discrimination

💡 Multi-agent reasoning improves uncertainty calibration in medical MCQA