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大型语言模型:在儿童近视方面开创新的教育前沿
Mohammad Delsoz1, Amr Hassan2, Amin Nabavi1
1Hamilton Eye Institute, Department of Ophthalmology, University of Tennessee Health Science Center, 930 Madison Ave., Suite 471, Memphis, TN, 38163, USA.
Ophthalmology and therapy
|April 21, 2025
概括
聊天GPT-4o (o1预览) 在创建高质量的儿童近视患者教育材料方面表现有前途,提高了可读性和准确性. 它还增强了现有的在线材料,使其对患者更易于理解和可操作.
科学领域:
- 医疗保健中的人工智能
- 医学沟通 医学沟通
- 眼科医生 眼科 眼科
背景情况:
- 患者教育材料 (PEMs) 对于治疗儿童近视至关重要.
- 评估大型语言模型 (LLM) 在生成和完善这些材料方面的有效性至关重要.
研究的目的:
- 评估ChatGPT-3.5,ChatGPT-4o (o1预览) 和Google Gemini在创建和改进儿童近视患者教育材料方面的表现.
- 通过使用既定的指标来评估LLM产生的内容的可读性和质量.
主要方法:
- 用三个提示生成和修改儿童近视的PEM.
- 评估了LLM输出的质量 (DISCERN),可读性 (FKGL,SMOG),可理解性/可操作性 (PEMAT) 和准确性.
- 进行了统计分析,以比较模型性能.
主要成果:
- 聊天GPT-4o (o1预览版) 和聊天GPT-3.5产生了优质的PEM,尽管质量略有下降,由于特定的可读性限制.
- 所有模型都产生了可理解的材料,但可操作性仍低于目标值.
- 通过有针对性的提示,可读性显著改善,ChatGPT-4o (o1预览) 显示了最大的收益.
结论:
- 聊天GPT-4o (o1预览) 是一个能够生成准确,高质量和易于理解的儿童近视患者教育材料的工具.
- 法律医疗学可以有效地提高现有的在线患者教育资源的可读性和质量.
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