人工智能生成内容在医学检查中的应用

IF 1.9 Q2 EDUCATION, SCIENTIFIC DISCIPLINES Advances in Medical Education and Practice Pub Date : 2025-02-25 eCollection Date: 2025-01-01 DOI:10.2147/AMEP.S492895
Rui Li, Tong Wu
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引用次数: 0

摘要

随着大型语言模型的快速发展,人工智能生成内容(AIGC)为构建医学检查问题提供了新的机会。然而,如何有效地利用AIGC来设计医学问题尚不清楚。AIGC具有反应速度快、效率高、模拟临床效果好等特点。在这项研究中,我们揭示了纸质考试固有的局限性,并提供了一个使用AIGC生成问题的简化指导,特别关注多项选择题、案例研究题和视频题。手动审查对于确保生成内容的准确性和质量仍然是必要的。未来的发展将受益于检索增强生成、多智能体系统和视频生成等技术。随着AIGC的不断发展,预计它将为医学考试带来革命性的变化,提高考试准备的质量,并有助于有效培养医学生。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Application of Artificial Intelligence Generated Content in Medical Examinations.

As the rapid development of large language model, artificial intelligence generated content (AIGC) presents novel opportunities for constructing medical examination questions. However, it is unclear about the way of effectively utilizing AIGC for designing medical questions. AIGC is characterized by its rapid response capabilities and high efficiency, as well as good performance in mimicking clinical realities. In this study, we revealed the limitations inherent in paper-based examinations, and provided a streamlined instruction for generating questions using AIGC, with a particular focus on multiple-choice questions, case study questions, and video questions. Manual review remains necessary to ensure the accuracy and quality of the generated content. Future development will be benefited from technologies like retrieval augmented generation, multi-agent system, and video generation technology. As AIGC continues to evolve, it is anticipated to bring transformative changes to medical examinations, enhancing the quality of examination preparation, and contributing to the effective cultivation of medical students.

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来源期刊
Advances in Medical Education and Practice
Advances in Medical Education and Practice EDUCATION, SCIENTIFIC DISCIPLINES-
CiteScore
3.10
自引率
10.00%
发文量
189
审稿时长
16 weeks
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