人工智能对骨质疏松症的洞察:评估ChatGPT的信息质量和可读性
Yakup Erden1, Mustafa Hüseyin Temel2, Fatih Bağcıer3
1Clinic of Physical Medicine and Rehabilitation, İzzet Baysal Physical Treatment and Rehabilitation Training and Research Hospital, Orüs Street, No. 59, 14020, Bolu, Turkey. yakuperden@hotmail.com.
关于骨质疏松症的ChatGPT回复存在重大质量和可读性问题. 这些信息需要先进的教育背景,未能满足医疗保健标准的患者理解.
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:
- 人工智能 (AI) 应用越来越多地用于健康信息检索.
- 准确和可读的健康信息对于患者在治疗骨质疏松症等疾病方面的赋权至关重要.
- 骨质疏松症是一个主要的公共卫生问题,需要可访问的患者资源.
研究的目的:
- 评估关于骨质疏松症的ChatGPT生成响应的质量和可读性.
- 评估人工智能产生的健康信息是否符合既定的患者教育标准.
主要方法:
- 使用谷歌趋势识别了经常搜索的骨质疏松症相关的关键词.
- 在ChatGPT中输入38个关键词以生成响应.
- 使用确保患者质量信息 (EQIP) 评估响应质量,使用弗莱什-金凯德等级水平 (FKGL) 和阅读方便 (FKRE) 评估可读性.
主要成果:
- 聊天GPT的回复显示"质量存在严重问题" (EQIP平均得分:48.71).
- 可读性得分表明高水平的复杂性 (平均FKGL:13.25,平均FKRE:28.71),表明需要17年的教育.
- 在响应质量 (EQIP) 和可读性 (FKGL,FKRE) 之间没有发现显著的相关性.
结论:
- 聊天GPT很容易获得骨质疏松症信息,但不符合当前医疗保健标准的质量和可读性.
- 人工智能产生的骨质疏松症信息的复杂性可能会阻碍患者的理解和自我管理.
- 需要进一步发展,以确保人工智能产生的健康内容准确,易于访问和易于理解.
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