临床瘤学中的人工智能:从提高生产力到创造性发现
Masahiro Kuno1,2, Hiroki Osumi1, Shohei Udagawa1
1Department of Gastroenterological Chemotherapy, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo 135-8550, Japan.
Current oncology (Toronto, Ont.)
|November 26, 2025
概括
人工智能 (AI) 对于管理复杂的癌症数据,提高生产力和在瘤学中实现新发现至关重要. 未来人工智能框架指导了在临床实践中负责任地实施人工智能.
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:
- 临床瘤学正在与压倒性的数据复杂性作斗争.
- 人工智能 (AI) 的整合正在成为现代癌症护理的必要条件.
- 人工智能为提高生产力和推动创造性发现提供了潜在的解决方案.
研究的目的:
- 审查人工智能对癌症护理生产力和发现的双重影响.
- 分析AI的演变和临床应用,从机器学习到基础模型.
- 引入FUTURE-AI框架,用于对AI进行负责任的临床转化.
主要方法:
- 对人工智能发展的审查 (机器学习,深度学习,基础模型).
- 在诊断任务,文档和研究工作流程中分析AI应用.
- 检查人工智能用于多式联运数据集成,生物标志物识别和药物开发.
主要成果:
- 人工智能通过诊断,文档和研究的自动化来提高生产力.
- 人工智能通过识别计算生物标志物和患者子组来促进创造性发现.
- 人工智能加速药物开发和研究工作流程.
结论:
- 人工智能对于克服瘤学的数据复杂性至关重要.
- 以FUTURE-AI等框架为指导的负责任的AI部署,增强了临床判断力,并保持了以患者为中心的护理.
- 人工智能集成对于推进癌症治疗和研究至关重要.
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