人工智能聊天机器人在瘤学中的医疗准确性:一个范围审查
David Chen1,2, Kate Avison1,3, Saif Alnassar1,3
1Princess Margaret Hospital Cancer Centre, Radiation Medicine Program, Toronto, ON M5G 2C4, Canada.
The oncologist
|April 26, 2025
概括
大型语言模型 (LLM) 在瘤学中显示出信息检索和决策支持的前景. 需要进一步的研究来确保准确性和通用性,强调临床医生对这些AI工具的监督的必要性.
科学领域:
- 在瘤学中使用人工智能
- 医疗信息学 医疗信息学
- 临床决策支持系统 临床决策支持系统
背景情况:
- 大型语言模型 (LLM) 展示了先进的自然语言处理能力.
- 在瘤学中,LLM正在探索数据解释和临床决策支持.
- 潜在的应用包括改善临床结果和提供信息资源.
研究的目的:
- 审查目前在瘤学LLM应用程序的医疗准确性.
- 确定瘤学LLM的研究趋势和未来的研究领域.
主要方法:
- 在Ovid Medline上对2000年以来的研究进行了范围范围的文献搜索.
- 包括的研究评估了LLMs在瘤学环境中的医学准确性.
- 提取了研究特征和结果,以绘制瘤学LLM景观.
主要成果:
- 包括60项研究,主要评估LLM作为健康信息资源 (48%),诊断 (20%) 和管理 (17%).
- 微调和快速工程LLM的研究从2022-2024年增加.
- 优点包括准确的信息,减少工作量和改善可访问性;缺点涉及可靠性问题和幻觉,需要临床医生监督.
结论:
- 人们对在瘤学中应用LLM非常感兴趣,特别是在医疗信息和决策支持方面.
- 在外部数据集中进行进一步验证对于概括性和更高的准确性至关重要.
- 临床监督对于在各种临床场景中安全有效地使用LLM至关重要.
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