在瘤学中面临大型语言模型的患者:叙述性审查
Charles Raynaud1, David Wu2, Jarod Levy3
1Department of Radiation Oncology, Hôpital Européen Georges Pompidou, Assistance Publique-Hôpitaux de Paris, Paris, France.
JCO clinical cancer informatics
|November 8, 2024
概括
大型语言模型 (LLM) 正在通过加强患者教育,诊断和治疗监测来彻底改变癌症护理. 本综述探讨了在瘤学中使用LLM的好处和挑战.
科学领域:
- 在瘤学瘤学.
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 大型语言模型 (LLM) 代表了人工智能的重大进步.
- 它们在医疗保健中的应用正在迅速扩大,特别是在瘤学等专业领域.
- 患者越来越多地在整个癌症过程中寻求可访问的信息和支持.
研究的目的:
- 审查目前LLMs在瘤领域的患者护理中的应用.
- 确定LLM整合对癌症患者的潜在好处.
- 检查围绕LLM在瘤学中的使用的伦理和监管方面的考虑.
主要方法:
- 对瘤学LLM研究的系统文献综述.
- 分析目前在整个患者旅程 (教育,诊断,监测,后续) 中的LLM应用.
- 评估报告的好处,挑战和伦理影响.
主要成果:
- 正在利用LLM进行患者教育,症状跟踪和治疗坚持支持.
- 潜在的好处包括个性化信息,改善沟通和增强患者参与.
- 重要的伦理考虑包括数据隐私,算法偏见和监管框架的需要.
结论:
- 在改变瘤患者体验方面,LLM具有重大前景.
- 应对道德和监管方面的挑战对于负责任和有效的实施至关重要.
- 需要进一步的研究来优化LLM整合到常规瘤护理中.
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