mlsanityData to 7 Oct 2026

AI-assisted workflow enables rapid, high-fidelity breast cancer clinical trial eligibility prescreening

arXiv 2511.05696 ↗First posted 7 Nov 2025cs.LGcited by 0

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Abstract (arXiv)

Clinical trials play an important role in cancer care and research, yet participation rates remain low. We developed MSK-MATCH (Memorial Sloan Kettering Multi-Agent Trial Coordination Hub), an AI system for automated eligibility screening from clinical text. MSK-MATCH integrates a large language model with a curated oncology trial knowledge base and retrieval-augmented architecture providing explanations for all AI predictions grounded in source text. In a retrospective dataset of 88,518 clinical documents from 731 patients across six breast cancer trials, MSK-MATCH automatically resolved 61.9% of cases and triaged 38.1% for human review. This AI-assisted workflow achieved 98.6% accuracy, 98.4% sensitivity, and 98.7% specificity for patient-level eligibility classification, matching or exceeding performance of the human-only and AI-only comparisons. For the triaged cases requiring manual review, prepopulating eligibility screens with AI-generated explanations reduced screening time from 20 minutes to 43 seconds at an average cost of 0.96 per patient-trial pair.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 19 of its 61 references that are in the map. First posted on arXiv 7 Nov 2025.

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References · 19

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7 more
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  1. 2025TrialMatchAI: An End-to-End AI-powered Clinical Trial Recommendation System to Streamline Patient-to-Trial Matching
  2. 2025Toward an AI Reasoning-Enabled System for Patient-Clinical Trial Matching
  3. 2026Eligibility-Aware Evidence Synthesis: An Agentic Framework for Clinical Trial Meta-Analysis
  4. 2025Smart Trial: Evaluating the Use of Large Language Models for Recruiting Clinical Trial Participants via Social Media
  5. 2023LeafAI: query generator for clinical cohort discovery rivaling a human programmer
  6. 2026Skill-Augmented AI Agents for Medical Research Analysis: An Exploratory Multi-Model Human Evaluation in an NSCLC Transcriptomic Biomarker Task
  7. 2023Improving Patient Pre-screening for Clinical Trials: Assisting Physicians with Large Language Models
  8. 2026Retrieval-Augmented LLMs for Evidence Localization in Clinical Trial Recruitment from Longitudinal EHR Narratives