评估不同人工智能聊天机器人模型提供的关于甲状腺功能低下症的信息的准确性,质量和可读性
Ting Ruan1, Xinran Shao2, Yihan Sun3
1Liaoning University of Traditional Chinese Medicine, Shenyang, China.
Frontiers in public health
|December 26, 2025
概括
领先的AI聊天机器人提供准确和高质量的甲状腺功能低下症信息,但它们复杂的可读性可能会阻碍患者的教育. 为了更广泛的健康应用,需要进一步优化.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 内分泌学 在内分泌学.
背景情况:
- 人工智能聊天机器人越来越多地用于健康信息.
- 评估人工智能产生的医疗内容的准确性和质量至关重要.
- 甲状腺功能低下症的诊断,治疗和风险是患者理解的关键领域.
研究的目的:
- 评估人工智能聊天机器人对成人甲状腺功能低下症的反应的准确性,质量和可读性.
- 将ChatGPT-3.5,DeepSeek-V3和谷歌双子座-2.5与临床指南进行比较.
- 确定人工智能在提供甲状腺功能低下信息方面的潜力和局限性.
主要方法:
- 根据临床指南制定了27个关于甲状腺功能低下症诊断,治疗和风险的问题.
- 通过使用利克特尺度对准确度和DISCERN对质量进行评估AI反应.
- 通过使用Flesch阅读易度,Flesch-Kincaid等级水平,炮雾指数和SMOG来评估可读性.
主要成果:
- 所有的人工智能模型都实现了高精度 (平均>4.5) 和质量 (率>94%) .
- 整体质量没有显著差异,但Gemini-2.5对治疗问题的质量较低.
- 人工智能反应难以理解,需要大学水平的教育 (低FRE,高FKGL/GFI).
结论:
- 人工智能聊天机器人可以根据指南生成准确,高质量的甲状腺功能低下症信息.
- 人工智能输出的高阅读难度可能会限制患者教育实用性.
- 未来的研究应该专注于改善人工智能输出可读性,以更广泛的健康教育应用.
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