临床瘤学的基础模型:进展和前景
1Department of Precision Medicine, Changhai Hospital, Second Military Medical University (Naval Medical University), Shanghai, 200433, China.
Cancer letters
|December 17, 2025
概括
基础模型 (FMs) 通过分析多式联络数据,有望通过分析多式联络数据来推进癌症治疗. 克服数据异质性,隐私问题和偏见对于开发可靠,可泛化的人工智能工具至关重要.
科学领域:
- 在瘤学瘤学.
- 人工智能的人工智能
- 生物医学数据科学 生物医学数据科学
背景情况:
- 癌症是一个重大的全球健康挑战,随着各种数据 (病理学,放射学,基因组学,EHRs) 的快速增加.
- 基础模型 (FMs) 正在成为癌症查,诊断,结果预测和治疗选择的强大工具.
研究的目的:
- 审查基础模型在瘤学的潜力.
- 确定阻碍开发和实施支持FM的癌症护理工具的关键障碍.
- 提出克服这些挑战的策略.
主要方法:
- 审查瘤学基础模型的当前应用和挑战.
- 分析数据异质性,注释稀缺性,监管障碍,隐私问题和潜在的偏见.
- 讨论协作方法和数据基础设施要求.
主要成果:
- 基础模型在各种瘤学任务中提供了变革性的潜力,从诊断到临床试验设计.
- 显著的障碍包括数据变化,有限的高质量注释队列,不断变化的法规,数据隐私和算法偏差.
- 跨机构伙伴关系和强大的数据基础设施对于进步至关重要.
结论:
- 解决数据质量,标准化,隐私和公平性至关重要,以实现FM在癌症护理中的全部潜力.
- 在临床团队中嵌入人工智能专业知识的协作努力对于开发可泛化和可信赖的AI解决方案至关重要.
- FM的战略整合有望重塑瘤实践的未来.
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