通过为医生提供ChatGPT培训,加强发展中国家儿童喘管理:一种随机对照试验
Liwen Zhang1, Guijun Yang1, Jiajun Yuan2
1Department of Respiratory Medicine, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Frontiers in pediatrics
|July 18, 2025
概括
在中国使用ChatGPT培训医生显著提高了儿童喘管理技能. 这突出了大型语言模型 (LLM) 作为医疗教育在服务不足地区的有价值的工具.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 儿科肺病学 儿科肺病学
背景情况:
- 儿童喘是一个全球性的健康问题,特别是在欠发达地区.
- 大型语言模型 (LLM) 显示了增强医疗服务的潜力.
研究的目的:
- 评估ChatGPT在改善医生儿童喘管理技能的有效性.
- 评估基于LLM的培训在资源有限的环境中的影响.
主要方法:
- 一项随机对照试验,涉及中国192名医生.
- 对照组 (传统培训) 与干预组 (ChatGPT培训) 的比较.
- 评估包括培训前,培训后和2周后续评估.
主要成果:
- 聊天GPT干预组在测试得分上表现出显著的改善 (72±8比50±9).
- 在干预组中,经常使用ChatGPT的比例从6.3%增加到62%.
- 医生报告了更高的满意度,熟悉度和使用ChatGPT的意图.
结论:
- 聊天GPT培训有效地提高了医生在治疗儿童喘方面的技能.
- 像ChatGPT这样的LLM是医疗培训在服务不足地区的宝贵教育工具.
- 需要对LLM整合和患者结果进行进一步的研究.
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