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AI-SC Multi-center Study
Sponsor: University Health Network, Toronto
Summary
To examined the opportunity for Artificial Intelligence (AI) agents to evaluate transplant candidacy objectively at LT-SC, with a large language models (LLM) representing the expertise of each individual specialist (hepatologist, surgeon, anesthesiologist, psychiatrist and social worker) and coming up with a group consensus decision upon inter-agent communication using prompts GPT-4 in OpenAI (private version).
Official title: Evaluation of a Multi-Agent AI Selection Committee for Objective Assessment of Liver Transplant Candidacy
Key Details
Gender
All
Age Range
18 Years - 70 Years
Study Type
OBSERVATIONAL
Enrollment
1000
Start Date
2026-04-01
Completion Date
2027-12-31
Last Updated
2026-10-26
Healthy Volunteers
No
Conditions
Interventions
evaluate the alignment between AI-SC recommendations and LT-SC decisions
To validate the developed model, investigators invited other collaborating centers, including Vancouver Coastal Health (Canada), Mayo Clinic (US), John Hopkins Hospital (US), Royal Prince Alfred Hospital (AU), National University of Singapore (Singapore), UCSF Health (US), Vanderbilt University Medical Center (US), John Hopkins Hospital (US), MeDanTa (India), and Ministry of National Guard Health Affairs (Saudi Arabia) to perform a validation as an extension of data governance phase.
Multi AI-SC model
To evaluate the feasibility and acceptability of integrating such multi AI-SC(Selection Committee) agents into LT candidate assessments.
Locations (1)
Toronto General Hospital
Toronto, Ontario, Canada