Article

Med-ICE: Enhancing Factual Accuracy in Medical AI through Autonomous Multi-Agent Consensus

2026-04-04

Abstract excerpt

The integration of Large Language Models into high-stakes clinical workflows is critically hampered by their lack of verifiable reliability and tendency to generate hallucinations. This paper introduces Med-ICE, an autonomous framework designed to enhance the reliability of LLMs for medical applications. Med-ICE adapts the Iterative Consensus Ensemble paradigm, enabling a group of peer LLM agents to collaborativel...

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Literature Corpus work: e9769a8b-d7b7-519d-9586-99c9ddef36ba
DOI: 10.64898/2026.04.02.26350080

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