课堂在会议中:分析GPT-4创建的整形外科在职检查问题
Daniel Najafali1, Logan G Galbraith2, Justin M Camacho3
1From the Carle Illinois College of Medicine, University of Illinois Urbana-Champaign, Urbana, Ill.
Plastic and reconstructive surgery. Global open
|September 20, 2024
概括
生成式预训练变压器4 (GPT-4) 可以创建整形外科在职培训考试 (PSITE) 实践问题,但质量很差. 虽然人工智能显示出作为教育工具的潜力,但人类监督对准确性至关重要.
科学领域:
- 医学教育 医学教育
- 人工智能在医学中的应用
- 进行外科手术培训.
背景情况:
- 整形外科在职培训考试 (PSITE) 对于住院评估至关重要.
- 对PSITE的有效准备要求居民花费大量的学习时间.
- 这项研究评估了生成预训练变压器4 (GPT-4) 产生PSITE风格实践问题的能力.
研究的目的:
- 评估GPT-4能够为PSITE生成多选择题的能力.
- 与实际PSITE考试相比,分析GPT-4生成问题的可读性和质量.
- 确定GPT-4作为整形外科住院医生补充研究工具的潜在实用性.
主要方法:
- 提示GPT-4在所有PSITE部分创建多选题.
- 产生的问题包括答案选择和详细的理由.
- 分析了可读性指标 (例如,Flesch-Kincaid) 和整体质量,并与2022年PSITE.com进行了比较.
主要成果:
- GPT-4产生的问题可读性比2022年PSITE (50.35) 低 (Flesch-Kincaid中位数为43.90).
- 与2022年PSITE相比,GPT-4问题要简单得多,句子,单词和复杂单词要少.
- 总体而言,GPT-4产生的问题质量被认为很差,有事实上的不准确性和错误的解释.
结论:
- GPT-4可以生成PSITE实践问题,但它们的质量目前不足以独立使用.
- 人工智能展示了创建教育内容的潜力,但由于不准确性,需要仔细监督.
- 在经验丰富的外科医生的监督下,GPT-4可以作为美容手术培训的宝贵辅助.
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