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Recruiting NCT06935253
Large Language Models To Improve the Quality of Care of Cardiology Patients
Trial Parameters
Condition Hypertrophic Cardiomyopathy (HCM)
Sponsor Stanford University
Study Type INTERVENTIONAL
Phase N/A
Enrollment 12
Sex ALL
Min Age 18 Years
Max Age N/A
Start Date 2025-01-10
Completion 2025-11
All Conditions
Interventions
Large Language Model
Brief 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 Criteria
Inclusion Criteria: * Board certified or board eligible Cardiologist. Exclusion Criteria: * Not currently practicing clinically