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.
Hypertrophic Cardiomyopathy (HCM), Cardiomyopathy, Genetic Disease, Cardiology
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.
Large Language Models To Improve the Quality of Care of Cardiology Patients
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Stanford, Palo Alto, California, United States, 94303
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
For general information about clinical research, read Learn About Studies.
18 Years to
ALL
No
Stanford University,
Euan A Ashley, BSc, MB ChB, DPhil, PRINCIPAL_INVESTIGATOR, Stanford University
2025-06