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ChatGPT在德国妇产科考试中的表现——为人工智能强化医学教育和临床实践铺平道路。

ChatGPT's performance in German OB/GYN exams - paving the way for AI-enhanced medical education and clinical practice.

作者信息

Riedel Maximilian, Kaefinger Katharina, Stuehrenberg Antonia, Ritter Viktoria, Amann Niklas, Graf Anna, Recker Florian, Klein Evelyn, Kiechle Marion, Riedel Fabian, Meyer Bastian

机构信息

Department of Gynecology and Obstetrics, Klinikum Rechts der Isar, Technical University Munich (TU), Munich, Germany.

Department of Gynecology and Obstetrics, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen, Germany.

出版信息

Front Med (Lausanne). 2023 Dec 13;10:1296615. doi: 10.3389/fmed.2023.1296615. eCollection 2023.

Abstract

BACKGROUND

Chat Generative Pre-Trained Transformer (ChatGPT) is an artificial learning and large language model tool developed by OpenAI in 2022. It utilizes deep learning algorithms to process natural language and generate responses, which renders it suitable for conversational interfaces. ChatGPT's potential to transform medical education and clinical practice is currently being explored, but its capabilities and limitations in this domain remain incompletely investigated. The present study aimed to assess ChatGPT's performance in medical knowledge competency for problem assessment in obstetrics and gynecology (OB/GYN).

METHODS

Two datasets were established for analysis: questions (1) from OB/GYN course exams at a German university hospital and (2) from the German medical state licensing exams. In order to assess ChatGPT's performance, questions were entered into the chat interface, and responses were documented. A quantitative analysis compared ChatGPT's accuracy with that of medical students for different levels of difficulty and types of questions. Additionally, a qualitative analysis assessed the quality of ChatGPT's responses regarding ease of understanding, conciseness, accuracy, completeness, and relevance. Non-obvious insights generated by ChatGPT were evaluated, and a density index of insights was established in order to quantify the tool's ability to provide students with relevant and concise medical knowledge.

RESULTS

ChatGPT demonstrated consistent and comparable performance across both datasets. It provided correct responses at a rate comparable with that of medical students, thereby indicating its ability to handle a diverse spectrum of questions ranging from general knowledge to complex clinical case presentations. The tool's accuracy was partly affected by question difficulty in the medical state exam dataset. Our qualitative assessment revealed that ChatGPT provided mostly accurate, complete, and relevant answers. ChatGPT additionally provided many non-obvious insights, especially in correctly answered questions, which indicates its potential for enhancing autonomous medical learning.

CONCLUSION

ChatGPT has promise as a supplementary tool in medical education and clinical practice. Its ability to provide accurate and insightful responses showcases its adaptability to complex clinical scenarios. As AI technologies continue to evolve, ChatGPT and similar tools may contribute to more efficient and personalized learning experiences and assistance for health care providers.

摘要

背景

聊天生成预训练变换器(ChatGPT)是OpenAI于2022年开发的一种人工智能学习和大语言模型工具。它利用深度学习算法处理自然语言并生成回答,使其适用于对话界面。目前正在探索ChatGPT在改变医学教育和临床实践方面的潜力,但其在该领域的能力和局限性仍未得到充分研究。本研究旨在评估ChatGPT在妇产科(OB/GYN)问题评估的医学知识能力方面的表现。

方法

建立了两个数据集进行分析:(1)来自德国一家大学医院妇产科课程考试的问题,以及(2)来自德国医学国家许可考试的问题。为了评估ChatGPT的表现,将问题输入聊天界面,并记录回答。定量分析将ChatGPT的准确性与不同难度水平和问题类型的医学生的准确性进行了比较。此外,定性分析评估了ChatGPT回答在易于理解、简洁性、准确性、完整性和相关性方面的质量。对ChatGPT产生的非明显见解进行了评估,并建立了见解密度指数,以量化该工具为学生提供相关和简洁医学知识的能力。

结果

ChatGPT在两个数据集中都表现出一致且可比的性能。它给出正确回答的比率与医学生相当,从而表明其能够处理从一般知识到复杂临床病例呈现的各种问题。该工具的准确性在一定程度上受医学国家考试数据集中问题难度的影响。我们的定性评估表明,ChatGPT提供的答案大多准确、完整且相关。ChatGPT还提供了许多非明显见解,尤其是在正确回答的问题中,这表明其在增强自主医学学习方面的潜力。

结论

ChatGPT有望成为医学教育和临床实践中的辅助工具。其提供准确且有见地回答的能力展示了其对复杂临床场景的适应性。随着人工智能技术不断发展,ChatGPT和类似工具可能有助于为医疗保健提供者提供更高效和个性化的学习体验及帮助。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/494a/10753765/5505ef6b3fef/fmed-10-1296615-g001.jpg

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