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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Publication Details

Journal
Advances in Medical Education and Practice
Published
2025-02-01
DOI
https://doi.org/10.2147/amep.s492895
Citations
4
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
2.62

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article

Application of Artificial Intelligence Generated Content in Medical Examinations

Rui Li, Tong Wu
4 citations
Advances in Medical Education and Practice
Artificial Intelligence in Healthcare and Education
2.62
article

Application of Artificial Intelligence Generated Content in Medical Examinations

Rui Li, Tong Wu
article en
4 citations

Abstract

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.

Advances in Medical Education and PracticeVol. Volume 16
Tongji Hospital (CN), Huazhong University of Science and Technology (CN)
Huazhong University of Science and Technology, Tongji University, Tongji Medical College, Huazhong University of Science and Technology
Quality Education
Openalex Percentile: Top 10%
Artificial Intelligence in Healthcare and Education
2.62
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Application of Artificial Intelligence Generated Content in Medical Examinations — Rui Li, Tong Wu · Advances in Medical Education and Practice (2025) | TGRS Research Map | TGRS