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生成性语言模型和开放注释:探索承诺和局限性

Charlotte Blease^1,2, John Torous², Brian McMillan³

¹Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden.

JMIR medical education

|January 4, 2024

概括

患者在线记录访问 (ORA) 对临床文档有好处,但也带来了挑战. 生成型人工智能 (AI) 提供了一种潜在的解决方案,可以提高笔记的清晰度和准确性,并减少临床医生的工作量.

科学领域:

医疗信息学医疗信息学
医疗文件医疗文件
医疗保健中的人工智能

背景情况:

患者在线记录访问 (ORA) 正在全球范围内扩大,为患者提供全面的健康信息,包括临床笔记.
这种增加的访问需要改变临床文档实践,引发了对准确性,完整性和临床医生的工作负载的担忧.
现有的挑战包括为患者的可读性调整文档,以及管理临床医生在笔记和查询上花费时间的潜在增加.

研究的目的:

探索当前的方法,以应对由于患者在线记录访问的临床文档方面的挑战.
提出生成人工智能 (AI) 作为一种新的策略,以支持临床医生创建患者友好的叙事总结.
检查将生成AI整合到临床笔记文档中的潜在好处和风险.

主要方法:

这篇观点论文回顾了有关患者在线记录访问的现有文献及其对临床文档的影响.
它讨论了建议的临床医生和患者教育策略.
它介绍并评估了生成人工智能的潜在应用,以增强临床笔记总结.

主要成果:

生成型人工智能可以提高临床笔记的清晰度,准确性和以患者为中心.
人工智能有可能减轻临床医生的文档工作负担.
当前的生成人工智能技术具有相关的风险,需要仔细考虑.

结论:

生成性人工智能在患者在线记录访问时代为优化临床文档提供了一个有希望的长期战略.
成功的整合需要专注于联合创建临床笔记,并充分支持使用人工智能工具的临床医生.
解决风险和确保临床医师培训对于利用AI在改善患者沟通和护理方面的潜力至关重要.

关键词:

聊天GPT 聊天在GPT 聊天打开笔记打开笔记临床文档临床文档沟通工具是一种沟通工具.文件文档文档文件文档同理心同理心同情心生成性语言模型的模型.语言模型语言模型大型语言模型.医学教育医学教育在线记录访问在线记录访问.以患者为中心的护理.

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