Evaluating the efficacy of major language models in providing guidance for hand trauma nerve laceration patients:a case study on Google’s AI BARD,Bing AI,and ChatGPT  

作　　者：Bryan Lim Ishith Seth Gabriella Bulloch Yi Xie David J Hunter-Smith Warren M Rozen 

机构地区：[1]Department of Plastic Surgery,Peninsula Health,Melbourne 3199,Australia [2]Central Clinical School at Monash University,The Alfred Centre,Melbourne 3004,Australia [3]Faculty of Medicine and Surgery,The University of Melbourne 3053,Australia

出　　处：《Plastic and Aesthetic Research》2023年第1期758-768,共11页整形与美容研究（英文版）

摘　　要：This study evaluated three prominent Large Language Models(LLMs)-Google’s AI BARD,Bing’s AI,and ChatGPT-4 in providing patient advice for hand laceration.Five simulated patient inquiries on hand trauma were prompted to them.A panel of Board-certified plastic surgical residents evaluated the responses for accuracy,comprehensiveness,and appropriate sources.Responses were also compared against existing literature and guidelines.This study suggests that ChatGPT outperforms BARD and Bing AI in providing reliable,evidence-based clinical advice,but they still face limitations in depth and specificity.Healthcare professionals are essential in interpreting LLM recommendations,and future research should improve LLM performance by integrating specialized databases and human expertise to advance nerve injury management and optimize patient-centred care.

关 键 词：Artificial intelligence ChatGPT BARD Bings AI large language model nerve injury 

分 类 号：R65[医药卫生—外科学]