医学中的大型语言模型:临床应用,技术挑战和道德考虑
1Department of Medical Device Management and Research, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, Korea.
Healthcare informatics research
|May 19, 2025
概括
大型语言模型 (LLM) 在医疗保健中对辅助临床医生来说是有前途的,但面临着重大的技术和伦理挑战. 严格的验证和人类监督对于安全和公平的融合至关重要.
科学领域:
- 人工智能在医学中的应用
- 临床信息学 临床信息学
- 生物医学伦理 生物医学伦理
背景情况:
- 大型语言模型 (LLM) 越来越多地被用于医疗领域的各种应用.
- 了解当前的能力,局限性和伦理影响对于负责任的采用至关重要.
研究的目的:
- 在医学中对LLMs的临床应用进行全面的审查.
- 识别和分析与LLM实施相关的技术挑战.
- 检查在医疗保健中使用LLM的伦理考虑.
主要方法:
- 对同行评审的文章,技术报告和专家评论进行了系统的文献调查.
- 确定和分析了关键的临床应用,技术限制 (准确性,验证,透明度) 和伦理问题 (偏见,安全性,隐私).
主要成果:
- 在临床文档,决策支持,患者沟通和工作流程优化方面,LLM显示出潜力.
- 技术挑战包括模型幻觉,验证缺陷,集成复杂性和透明度问题.
- 伦理问题包括算法偏见,患者安全风险,问责缺陷和数据隐私.
结论:
- 在医学上,LLM提供了变革性的潜力,以增强临床医生的能力.
- 实质性的技术和道德障碍需要严格的研究,验证,明确的指导方针和人类监督.
- 现有证据支持LLM的辅助作用,优先考虑安全和公平.
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