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Advancing medical education in cervical cancer control with large language models for multiple-choice question generation
1
Zitationen
9
Autoren
2025
Jahr
Abstract
LLMs can generate MCQs comparable to clinician-generated ones with engineered prompts, though clinicians outperformed in cognitive level. LLM-assisted MCQ generation could enhance efficiency but requires rigorous validation to ensure educational quality.
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Autoren
Institutionen
- Peking Union Medical College Hospital(CN)
- Chinese Academy of Medical Sciences & Peking Union Medical College(CN)
- Tencent (China)(CN)
- China Medical University(CN)
- Liaoning Cancer Hospital & Institute(CN)
- University of Electronic Science and Technology of China(CN)
- Chengdu Women's and Children's Central Hospital(CN)
- Shenzhen Maternity and Child Healthcare Hospital(CN)
- Southern Medical University(CN)
- People's Hospital of Xinjiang Uygur Autonomous Region(CN)
- Jiangnan University(CN)