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大型语言模型是否是有效的工具来为患者提供关于腰椎间盘的信息? 脊柱外科医生的观点脊柱外科医生的观点

Siegmund Lang¹, Jacopo Vitale², Tamás F Fekete²

¹Department of Trauma Surgery, University Hospital Regensburg, Regensburg, Germany.

|May 6, 2024

概括

大型语言模型 (LLM) 对腰椎间盘的患者教育有希望,提供了普遍令人满意的信息. 然而,准确度和评价者协议的变化需要进一步开发可靠的AI驱动的医疗保健通信.

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,特别是聊天机器人,正在改变医疗保健患者教育.
确保人工智能生成的医疗信息的可靠性和准确性对于患者的安全和理解至关重要.

研究的目的:

评估像ChatGPT和谷歌Bard这样的大型语言模型 (LLM) 在提供准确和可理解的腰椎间盘瘤患者教育方面的有效性.
根据专家外科医生的评估,评估LLM响应的质量.

主要方法:

选择了关于腰椎间盘的十个常见问题.
六位经验丰富的脊椎外科医生对三个LLM的答案进行了评分,这些标准包括详尽性,清晰性,同理心和长度.
统计分析包括Fleiss Kappa,Chi-square和弗里德曼测试.

主要成果:

27.2%的答案被评为优秀,43.9%的答案被评为满意的,只需提供最少的解释.
在LLM中没有发现总体评级的显著差异.
完整性,清晰度,同理心和长度的平均评分超过3.5/5,但无法实现评审者之间的可靠性.

结论:

椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘椎间盘
评估的变化和偶尔的不准确性凸显了持续改进和严格监督的必要性,特别是考虑到新的AI法规.
未来的研究应该专注于更先进的LLM,以加强医疗保健中的患者与医生的沟通.

关键词:

人工智能评估AI评估聊天GPT 聊天在GPT 聊天在谷歌上搜索Bard.大型语言模型.腰椎椎间盘的发生患者教育患者教育

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