在诊断后用于癌症途径的人工智能 (AI) 应用的前性评估:系统审查
Sheba Macheka1, Peng Yun Ng1, Ophira Ginsburg2
1Institute of Cancer Policy, King's College London Faculty of Life Sciences & Medicine, London, UK.
BMJ oncology
|January 31, 2025
概括
癌症护理中的人工智能 (AI) 显示出有限的临床准备能力和诊断之外的部署能力. 未来的研究必须优先考虑对现实世界的影响进行标准化,协作实施研究.
科学领域:
- 在瘤学瘤学.
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 在癌症治疗中的整合正在增加,这是由于人口结构的变化和技术进步.
- 然而,它在提高诊断之外的护理质量,效率和公平性方面的有效性仍然不清楚.
- 本综述侧重于人工智能在癌症诊断后的应用.
研究的目的:
- 系统地审查评估AI在癌症诊断后治疗途径中的前性研究.
- 评估人工智能工具的临床准备和部署能力.
- 确定使用的AI类型及其相关结果.
主要方法:
- 从2013年1月到2023年5月,在PubMed和Web of Science上进行了系统的文献搜索.
- 确定并评估了15篇文章,详细介绍了癌症诊断后癌症途径中潜在的AI评估.
- 质量评估包括偏差风险工具和实施分析 (时间,成本,资源).
主要成果:
- 大多数人工智能瘤学研究仍然是实验性的,缺乏潜在的临床验证或部署.
- 研究经常无法确定临床有效性或将AI有效性转化为切实的临床益处.
- 人工智能研究受到标准化和卫生系统互操作性缺乏的阻碍,执行和公平性分析经常缺失.
结论:
- 目前对AI在癌症诊断后护理中的临床证据有限.
- 在测量的人工智能疗效和有益的临床结果之间存在很大的差距.
- 未来的研究应该强调协作AI实施研究,遵守严格的标准,并与卫生系统集成.
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