Abstract

The article "ChatGPT Efficacy for Answering Musculoskeletal Anatomy Questions: A Study Evaluating Quality and Consistency between Raters and Timepoints" assesses the performance of ChatGPT 3.5 in answering musculoskeletal anatomy questions, highlighting variability in response quality and reproducibility. We raise several points that may add further insights into the study's findings. While ChatGPT and other Large Language Models (LLMs) show promise in medical education, several areas require further exploration. We emphasize the importance of using larger question sets and diverse formats, such as multiple-choice questions (MCQs), where ChatGPT has demonstrated more consistent performance in prior studies. Additionally, improvements in artificial intelligence (AI) models and the incorporation of updated anatomical databases could enhance response accuracy. The study also identifies ChatGPT's lack of anatomical specificity as a limitation, which may be addressed by training AI models on specialized anatomy datasets. In conclusion, while ChatGPT is not yet a fully reliable standalone resource, it might serve as a complementary tool when integrated with traditional methods. Further research is needed to optimize AI for anatomy education.

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