The emergence of ChatGPT as one of the most advanced chatbots and its ability to generate diverse data has given room for numerous discussions worldwide regarding its utility, particularly in advancing medical education and research. This study seeks to assess the performance of ChatGPT in medical biochemistry to evaluate its potential as an effective self-learning tool for medical students. This evaluation was carried out using the university examination question papers of both parts 1 and 2 of medical biochemistry which comprised theory and multiple choice questions (MCQs) accounting for a total of 100 in each part. The questions were used to interact with ChatGPT, and three raters independently reviewed and scored the answers to prevent bias in scoring. We conducted the inter-item correlation matrix and the interclass correlation between raters 1, 2, and 3. For MCQs, symmetric measures in the form of kappa value (a measure of agreement) were performed between raters 1, 2, and 3. ChatGPT generated relevant and appropriate answers to all questions along with explanations for MCQs. ChatGPT has “passed” the medical biochemistry university examination with an average score of 117 out of 200 (58%) in both papers. In Paper 1, ChatGPT has secured 60 ± 2.29 and 57 ± 4.36 in Paper 2. The kappa value for all the cross-analysis of Rater 1, Rater 2, and Rater 3 scores in MCQ was 1.000. The evaluation of ChatGPT as a self-learning tool in medical biochemistry has yielded important insights. While it is encouraging that ChatGPT has demonstrated proficiency in this area, the overall score of 58% indicates that there is work to be done. To unlock its full potential as a self-learning tool, ChatGPT must focus on generating not only accurate but also comprehensive and contextually relevant content.

中文翻译：

---

评估 ChatGPT 作为医学生物化学自学工具：医学大学本科考试的表现评估

ChatGPT 作为最先进的聊天机器人之一的出现及其生成不同数据的能力，为全球范围内关于其实用性的大量讨论提供了空间，特别是在推进医学教育和研究方面。本研究旨在评估 ChatGPT 在医学生物化学方面的表现，以评估其作为医学生有效自学工具的潜力。本次评价采用医学生物化学第一部分和第二部分的大学考试试卷进行，包括理论题和选择题（MCQ），每部分共100分。这些问题用于与 ChatGPT 进行交互，三名评分者独立审查并对答案进行评分，以防止评分出现偏差。我们在评分者 1、2 和 3 之间进行了项目间相关矩阵和类间相关性。对于 MCQ，在评分者 1、2 和 3 之间执行了 kappa 值（一致性度量）形式的对称度量。ChatGPT为所有问题生成相关且适当的答案以及 MCQ 的解释。 ChatGPT已经“通过”了医学生物化学大学考试，两篇试卷的平均分都是117分（满分200分）（58%）。在论文 1 中，ChatGPT 在论文 2 中获得了 60 ± 2.29 和 57 ± 4.36。MCQ 中评分者 1、评分者 2 和评分者 3 分数的所有交叉分析的 kappa 值为 1.000。 ChatGPT 作为医学生物化学自学工具的评估产生了重要的见解。虽然令人鼓舞的是，ChatGPT 在这一领域表现出了熟练程度，但 58% 的总分表明还有很多工作要做。为了释放其作为自学工具的全部潜力，ChatGPT 必须专注于生成不仅准确而且全面且与上下文相关的内容。