The purpose of this research study is to measure the effect on of a large language model interface on the usability, attitudes, and provider trust when using a machine learning algorithm-based clinical decision support system in the setting of bleeding from the upper gastrointestinal tract (upper GIB). Specifically, the investigators are looking to assess the optimal implementation of such machine learning algorithms in simulation scenarios to best engender trust and improve usability. Participants will be randomized to either machine learning algorithm alone or algorithm with a large language model interface and exposed to simulation cases of upper GIB.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Change in Attitudes Towards Machine Learning Algorithms in Clinical Care using UTAUT
Timeframe: Approximately 60 minutes
Clinician Decision Making of Triage of GI bleeding
Timeframe: Approximately 60 minutes