AI RESEARCH
Eligibility-Aware Evidence Synthesis: An Agentic Framework for Clinical Trial Meta-Analysis
arXiv CS.AI
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ArXi:2604.02678v1 Announce Type: cross Clinical evidence synthesis requires identifying relevant trials from large registries and aggregating results that account for population differences. While recent LLM-based approaches have automated components of systematic review, they do not end-to-end evidence synthesis. Moreover, conventional meta-analysis weights studies by statistical precision without considering clinical compatibility reflected in eligibility criteria.