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Large Language Models To Improve the Quality of Care of Cardiology Patients

RECRUITINGN/ASponsored by Stanford University
Actively Recruiting
PhaseN/A
SponsorStanford University
Started2025-01-10
Est. completion2025-11
Eligibility
Age18 Years+
Healthy vol.Accepted
Locations1 site
View on ClinicalTrials.gov →

NCT06935253

Summary

This study evaluates the impact of large language models (LLMs) versus traditional decision support tools on clinical decision-making in cardiology. General cardiologists will be randomized to manage real patient cases from a cardiovascular genetic cardiomyopathy clinic, with or without AI assistance. Each case will be assessed by two cardiologists, and their responses will be graded by blinded subspecialty experts using a standardized evaluation rubric.

Eligibility

Age: 18 Years+Healthy volunteers accepted
Inclusion Criteria:

* Board certified or board eligible Cardiologist.

Exclusion Criteria:

* Not currently practicing clinically

Conditions5

CardiologyCardiomyopathyGenetic DiseaseHeart DiseaseHypertrophic Cardiomyopathy (HCM)

Locations1 site

Stanford
Palo Alto, California, 94303
Jack W O'Sullivan, MD, PhD6503009129jackos@stanford.edu

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