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COMPLETED
NCT05816473
NA

Artificial Intelligent Clinical Decision Support System Simulation Center Study for Technology Acceptance

Sponsor: Yale University

View on ClinicalTrials.gov

Summary

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.

Official title: Artificial Intelligent Clinical Decision Support System Simulation Center Study: Trust and Usefulness of Machine Learning Risk Stratification Tool for Acute Gastrointestinal Bleeding Using the Technology Acceptance Model

Key Details

Gender

All

Age Range

Any - Any

Study Type

INTERVENTIONAL

Enrollment

108

Start Date

2023-05-23

Completion Date

2024-12-31

Last Updated

2026-05-22

Healthy Volunteers

Yes

Interventions

OTHER

LLM

Use of a Large Language Model (LLM) chatbot interface to Interact with the Machine Learning Algorithm and interpretability dashboard.

Locations (1)

Yale New Haven Hospital

New Haven, Connecticut, United States