cbib/TrialMatchAI

TrialMatchAI aims to leverage large language models (LLMs) to streamline patient matching with clinical trials based on unique patient characteristics and eligibility criteria

47
/ 100
Emerging

TrialMatchAI helps medical professionals and researchers quickly find the most suitable clinical trials for individual patients. You input patient medical profiles and a collection of clinical trial descriptions, and the system outputs a ranked list of trial recommendations tailored to each patient's unique characteristics. This is designed for clinical research coordinators, principal investigators, and healthcare providers involved in patient recruitment for trials.

Use this if you need an AI-powered system to efficiently match patients to clinical trials based on complex eligibility criteria, with transparent and explainable recommendations.

Not ideal if you are looking for medical advice or a tool that replaces direct consultation with qualified healthcare professionals.

clinical-trials patient-matching medical-research healthcare-management patient-recruitment
No Package No Dependents
Maintenance 10 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 15 / 25

How are scores calculated?

Stars

18

Forks

4

Language

Python

License

Last pushed

Feb 10, 2026

Commits (30d)

0

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