Letter: Performance of ChatGPT and GPT-4 on Neurosurgery Written Board Examinations

Abstract

To the Editor: I am writing regarding to the recently published article, titled "Performance of ChatGPT and GPT-4 on Neurosurgery Written Board Examinations" by Ali et al.1 The authors assessed the performance of 2 large language models, ChatGPT and GPT-4, on a simulated neurosurgical written board examination. They discovered that both ChatGPT and GPT-4 attained passing scores on the simulated neurosurgical written board examination. However, GPT-4 demonstrated significantly superior performance compared with ChatGPT and human question bank users. Besides evaluating the manuscript, we would like to provide additional insights and considerations for future research. First, as artificial intelligence (AI) models consistently exhibit performance surpassing human levels on standardized examinations, it necessitates a reassessment of the role of conventional testing methods and the potential requirement for novel evaluation strategies that incorporate the capabilities of AI. Second, the challenges that AI models encounter when processing imaging-based questions highlight the significance of incorporating advanced computer vision capabilities into AI models. This integration aims to improve their performance in image-based assessments. Third, gaining a deeper understanding of the relationship between question characteristics, such as word count and higher-order problem-solving, and the accuracy of AI models can inform the development of specific training and fine-tuning strategies. These strategies aim to overcome the identified limitations and improve the overall performance of AI models in neurosurgical assessments. Moreover, as AI models exhibit proficiency in answering standardized examination questions, it prompts inquiries into their potential role in clinical decision support. This highlights the necessity for rigorous validation and regulation to safeguard patient safety and ensure the ethical use of AI in health care. In conclusion, this study emphasizes the necessity for ongoing research and development in the integration of AI systems in medical education. It also highlights the crucial role of clinicians in comprehending the capabilities and limitations of these rapidly evolving technologies. We commend the authors for their valuable contribution to this important and rapidly advancing field.

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