在心血管健康,瘤和牛皮方面评估聊天机器人的响应质量和可读性:一项比较研究
Robert Olszewski1, Klaudia Watros2, Małgorzata Mańczak2
1Gerontology, Public Health and Education Department, National Institute of Geriatrics, Rheumatology and Rehabilitation, Warsaw, Poland; Department of Ultrasound, Institute of Fundamental Technological Research, Polish Academy of Sciences.
International journal of medical informatics
|July 26, 2024
概括
这项研究发现,大型语言模型 (LLM) 聊天机器人提供可靠的健康信息,但质量和可读性各不相同. 由于这些差异,患者应该核实聊天机器人生成的医疗建议.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
背景情况:
- 医疗保健系统面临人员短缺,患者越来越依赖聊天机器人获取医疗信息.
- 评估聊天机器人响应的质量和可靠性至关重要.
研究的目的:
- 评估医学主题受欢迎的大型语言模型 (LLM) 聊天机器人的响应的质量,可读性和准则合规性.
主要方法:
- 评估了五个可以免费访问的聊天机器人 (Gemini,微软Copilot,PiAI,ChatGPT,ChatSpot).
- 问题涵盖心脏病学,瘤学和牛皮,与临床指南相比,答案.
- 使用多个尺度评估可读性,医疗专业人员评价符合指导方针.
主要成果:
- 聊天机器人的响应在长度,可读性得分 (Flesch阅读易度,Flesch-Kincaid等级水平,炮火雾,Dale-Chall) 和准则遵守方面有显著差异.
- 可读性水平往往超过了标准的患者理解水平.
结论:
- LLM聊天机器人通常提供可靠的健康信息,但在输出质量和复杂性方面有所不同.
- 患者必须谨慎,并核实从聊天机器人获得的医疗信息,特别是在关键的健康决策.
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