Related Experiment Video
Updated: Jul 8, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
Published on: December 6, 2024
Battle of the Bots: Assessing the Ability of Four Large Language Models to Tackle Different Surgery Topics
1Department of Surgery, American University of Beirut Medical Center, Beirut, Lebanon.
Abstract:
ObjectiveOur study aims to compare the performance of different large language model chatbots on surgical questions of different topics and categories.Materials and MethodsFour different chatbots (ChatGPT 4.0, Medical Chat, Google Bard, and Copilot Ai) were used for our study. 114 multiple-choice surgical questions covering 9 different topics were entered into each chatbot, and their answers were recorded.ResultsThe performance of ChatGPT was significantly better than Bard (P < 0.0001) and Medical Chat (P = 0.0013) but not significantly better than Copilot (P = 0.9663). We also found a statistically significant difference in ENT (P = 0.0199) and GI (P = 0.0124) questions between each chatbot when we assessed their performances per surgical specialty. Finally, the mean scores of Bard, Copilot, Medical Chat, and ChatGPT 4.0 on the diagnosis questions were higher than those in the management questions. The difference was only statistically significant, however, for Bard (P = 0.0281).ConclusionOur study offers insight into the performance of different chatbots on surgery-related questions and topics. The strengths and shortcomings of each can provide us with a better understanding of how to use Chatbots in the surgical field, including surgical education.

