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Large Language Model-Assisted Point-in-Time Interpretation of Advanced Hemodynamics in Liver Transplant Recipients: A Pilot Evaluation of Content Quality and Safety
1
Zitationen
7
Autoren
2026
Jahr
Abstract
ChatGPT generated clinically acceptable, contextually aligned interpretations of complex intraoperative hemodynamic data in liver transplant recipients, with minimal evidence of unsafe recommendations. These findings suggest preliminary promise for LLM-assisted interpretation of advanced monitoring, while underscoring the need for future studies involving larger datasets, dynamic physiological inputs, and expanded evaluator groups. The reliability characteristics observed also provide initial support for further refinement and broader validation of the Delphi-derived ARQuAT framework.
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