mlsanityData to 14 Oct 2026

Matching Patients to Clinical Trials with Large Language Models

arXiv 2307.15051 ↗First posted 27 Jul 2023cs.CL cs.AIcited by 69

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Abstract (arXiv)

Patient recruitment is challenging for clinical trials. We introduce TrialGPT, an end-to-end framework for zero-shot patient-to-trial matching with large language models. TrialGPT comprises three modules: it first performs large-scale filtering to retrieve candidate trials (TrialGPT-Retrieval); then predicts criterion-level patient eligibility (TrialGPT-Matching); and finally generates trial-level scores (TrialGPT-Ranking). We evaluate TrialGPT on three cohorts of 183 synthetic patients with over 75,000 trial annotations. TrialGPT-Retrieval can recall over 90% of relevant trials using less than 6% of the initial collection. Manual evaluations on 1,015 patient-criterion pairs show that TrialGPT-Matching achieves an accuracy of 87.3% with faithful explanations, close to the expert performance. The TrialGPT-Ranking scores are highly correlated with human judgments and outperform the best-competing models by 43.8% in ranking and excluding trials. Furthermore, our user study reveals that TrialGPT can reduce the screening time by 42.6% in patient recruitment. Overall, these results have demonstrated promising opportunities for patient-to-trial matching with TrialGPT.

Key facts. Cited by 69 papers in the map (data through 14 Oct 2026). Builds on 27 of its 60 references that are in the map. First posted on arXiv 27 Jul 2023.

Builds on

27 of 60 references.

References · 27

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15 more
  1. 2020Self-Alignment Pretraining for Biomedical Entity Representationscited by 237
  2. 2022LinkBERT: Pretraining Language Models with Document Linkscited by 211
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Citing papers per year: 2023: 6; 2024: 24; 2025: 24; 2026: 15.

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  1. 2023A Survey of Large Language Models in Medicine: Progress, Application, and Challengecited by 124
  2. 2024MedCalc-Bench: Evaluating Large Language Models for Medical Calculationscited by 70
  3. 2024Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up Questionscited by 54
  4. 2024Zero-Shot Clinical Trial Patient Matching with LLMscited by 35
  5. 2024AI Hallucinations: A Misnomer Worth Clarifyingcited by 34
  6. 2025BIOMEDICA: An Open Biomedical Image-Caption Archive, Dataset, and Vision-Language Models Derived from Scientific Literaturecited by 34
  7. 2024Hidden flaws behind expert-level accuracy of multimodal GPT-4 vision in medicinecited by 31
  8. 2024Unmasking and Quantifying Racial Bias of Large Language Models in Medical Report Generationcited by 31
  9. 2024Large Language Models in Drug Discovery and Development: From Disease Mechanisms to Clinical Trialscited by 24
  10. 2024Mitigating the Risk of Health Inequity Exacerbated by Large Language Modelscited by 21
  11. 2023Distilling Large Language Models for Matching Patients to Clinical Trialscited by 16
  12. 2024Adversarial Attacks on Large Language Models in Medicinecited by 10
38 more
  1. 2024Panacea: A foundation model for clinical trial search, summarization, design, and recruitmentcited by 10
  2. 2023Ask Again, Then Fail: Large Language Models' Vacillations in Judgmentcited by 8
  3. 2023Large Language Models Illuminate a Progressive Pathway to Artificial Healthcare Assistant: A Reviewcited by 8
  4. 2024A Perspective for Adapting Generalist AI to Specialized Medical AI Applications and Their Challengescited by 8
  5. 2023TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Modelscited by 7
  6. 2023BioLORD-2023: Semantic Textual Representations Fusing LLM and Clinical Knowledge Graph Insightscited by 7
  7. 2025A Collection of Innovations in Medical AI for patient records in 2024cited by 7
  8. 2025Survey: Multi-Armed Bandits Meet Large Language Modelscited by 7
  9. 2024From RAGs to riches: Utilizing large language models to write documents for clinical trialscited by 6
  10. 2025RadOnc-GPT: An Autonomous LLM Agent for Real-Time Patient Outcomes Labeling at Scalecited by 5
  11. 2024PRISM: Patient Records Interpretation for Semantic Clinical Trial Matching using Large Language Modelscited by 4
  12. 2024Beyond Multiple-Choice Accuracy: Real-World Challenges of Implementing Large Language Models in Healthcarecited by 4
  13. 2025A Novel Ophthalmic Benchmark for Evaluating Multimodal Large Language Models with Fundus Photographs and OCT Imagescited by 4
  14. 2024Entry-level guide to the use of large language models for medical researchcited by 3
  15. 2024ACR: A Benchmark for Automatic Cohort Retrievalcited by 2
  16. 2024Can Large Language Models Replace Data Scientists in Biomedical Research?cited by 2
  17. 2025LLM-Match: An Open-Sourced Patient Matching Model Based on Large Language Models and Retrieval-Augmented Generationcited by 2
  18. 2025Real-world validation of a multimodal LLM-powered pipeline for High-Accuracy Clinical Trial Patient Matching leveraging EHR datacited by 2
  19. 2025Evaluation of Causal Reasoning for Large Language Models in Contextualized Clinical Scenarios of Laboratory Test Interpretationcited by 2
  20. 2026Med-V1: Small Language Models for Zero-shot and Scalable Biomedical Evidence Attributioncited by 2
  21. 2026Jev in Medicine: A Benchmark Evaluationcited by 2
  22. 2024CTBench: A Comprehensive Benchmark for Evaluating Language Model Capabilities in Clinical Trial Designcited by 1
  23. 2024Generative AI for Health Technology Assessment: Opportunities, Challenges, and Policy Considerationscited by 1
  24. 2025OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmologycited by 1
  25. 2025Enhancing Hepatopathy Clinical Trial Efficiency: A Secure, Large Language Model-Powered Pre-Screening Pipelinecited by 1
  26. 2025Systematic Literature Review on Clinical Trial Eligibility Matchingcited by 1
  27. 2025The potential role of AI agents in transforming nuclear medicine research and cancer management in Indiacited by 1
  28. 2025Recommending Clinical Trials for Online Patient Cases using Artificial Intelligencecited by 1
  29. 2025Aligning Large Language Models with Healthcare Stakeholders: A Pathway to Trustworthy AI Integrationcited by 1
  30. 2025TrialMatchAI: An End-to-End AI-powered Clinical Trial Recommendation System to Streamline Patient-to-Trial Matchingcited by 1
  31. 2025Diagnosing our datasets: How does my language model learn clinical information?cited by 1
  32. 2025Developing Large Language Models for Clinical Research Using One Million Clinical Trialscited by 1
  33. 2025Content-based 3D Image Retrieval and a ColBERT-inspired Re-ranking for Tumor Flagging and Stagingcited by 1
  34. 2025A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuningcited by 1
  35. 2026Agentic AI in Healthcare & Medicine: A Seven-Dimensional Taxonomy for Empirical Evaluation of LLM-based Agentscited by 1
  36. 2024HeCiX: Integrating Knowledge Graphs and Large Language Models for Biomedical Researchcited by 0
  37. 2024Novel Development of LLM Driven mCODE Data Model for Improved Clinical Trial Matching to Enable Standardization and Interoperability in Oncology Researchcited by 0
  38. 2024Can Artificial Intelligence Generate Quality Research Topics Reflecting Patient Concerns?cited by 0

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