肺栓塞教育:生成人工智能模型的作用
Rohma Zaidi1, Jonathan Asghedom1, Som Singh2
1University of Missouri Kansas City School of Medicine, Kansas City, Missouri.
Missouri medicine
|December 19, 2024
概括
像ChatGPT,Google Gemini和微软CoPilot这样的生成人工智能 (AI) 工具不符合美国患者健康信息可读性标准. 需要进一步的研究来评估AI.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 患者教育 患者教育
背景情况:
- 生成型人工智能 (AI) 越来越多地用于信息传播.
- 提高患者的健康素养至关重要,特别是在急性肺栓塞等复杂疾病中.
- 现有的文献探讨了人工智能在提高患者对疾病和管理的理解方面的潜力.
研究的目的:
- 评估生成AI响应对患者健康信息的可读性.
- 为了确定当前的AI模型是否符合美国的可读性建议.
主要方法:
- 评估公开可用的AI模型 (ChatGPT,谷歌Gemini,微软CoPilot) 所产生的响应的可读性.
- 将人工智能生成的内容与美国可读性标准进行比较.
主要成果:
- 聊天GPT,谷歌Gemini和微软CoPilot的响应不符合当前的美国可读性建议.
- 产生的内容可能会给患者的理解带来挑战.
结论:
- 目前,公开可用的生成性AI模型生产的健康信息并不容易为患者阅读.
- 纵向研究是必要的,以跟踪AI模型的可读性不断变化,因为它们通过深度学习来适应.
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