Large Language Models To Improve the Quality of Care of Cardiology Patients
Towards Bridging Generalists to Subspecialists With Large Language Models
Stanford University
12 participants
Jan 10, 2025
INTERVENTIONAL
Conditions
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
Inclusion Criteria1
- Board certified or board eligible Cardiologist.
Exclusion Criteria1
- Not currently practicing clinically
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Interventions
The intervention is a Large Language Model.
Locations(1)
View Full Details on ClinicalTrials.gov
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NCT06935253