聊天GPT和大型语言模型在医学和医疗保健中的应用:好处和陷
Andrew A Borkowski1,2,3, Colleen E Jakey1,2, Stephen M Mastorides1,2
1James A. Haley Veterans' Hospital, Tampa, Florida.
概括
大型语言模型 (LLM) 在医疗保健中为管理和诊断等任务提供了变革性的潜力. 然而,谨慎的伦理和隐私考虑对于其负责任的实施至关重要.
科学领域:
- 人工智能在医学中的应用
- 医疗信息学 医疗信息学
- 计算语言学 计算语言学
背景情况:
- 像ChatGPT这样的大型语言模型 (LLM) 在医疗保健中越来越多地被采用.
- 这些人工智能模型在广泛的数据集上进行训练,用于各种应用.
- 应用程序包括语言翻译,总结和回答问题.
研究的目的:
- 探索LLMs在医疗保健环境中的潜力.
- 确定与LLM整合相关的关键好处和挑战.
- 强调需要负责任和道德的部署.
主要方法:
- 审查目前在医疗保健LLMs的应用和能力.
- 对医疗专业人员和患者参与度的潜在影响的分析.
- 检查道德,隐私,安全和透明度方面的问题.
主要成果:
- 通过协助管理任务,LLM在改变医疗保健方面表现有前途.
- 提高诊断准确度和提高患者参与度的潜力.
- 显著的挑战包括区分事实和虚假信息,并确保数据隐私.
结论:
- 负责任和道德考虑对LLM在医学中的使用至关重要.
- 法律学代表着一个基本的技术进步,对医疗保健提供有广泛的影响.
- 要充分利用人工智能在医疗保健中的全部潜力,必须仔细应对挑战.
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