癌症中心的癌症信息学:分享如何构建人工智能准备的辐射瘤学信息学生态系统的想法.
Danielle S Bitterman1,2, Michael F Gensheimer3, David Jaffray4
1Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA.
JCO clinical cancer informatics
|December 6, 2023
概括
人工智能 (AI) 准备改变放射瘤学,利用庞大的数字数据. 癌症信息学领导者正在通过改进数据实践为人工智能集成做准备.
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:
- 癌症中心癌症信息学研讨会专注于2022年8月辐射瘤学的精准医学应用.
- 讨论涵盖了人工智能,生物标志物开发,决策支持,成像和辐射瘤学中的治疗学.
- 生成性AI的进步加速了AI在临床环境中的整合潜力.
研究的目的:
- 要突出2022年关于人工智能和辐射瘤学信息学研讨会的关键内容.
- 为数据采集,管理,表示和共享提供经验教训.
- 准备放射性瘤学领域,以安全有效地整合人工智能和信息学.
主要方法:
- 来自"精准医学在放射性瘤学中的应用"研讨会的演讲和讨论摘要.
- 分析与辐射瘤学数据处理和人工智能准备相关的主题.
- 对未来人工智能实施的研讨会发现的背景化.
主要成果:
- 放射性瘤学产生大量的数字数据,使其成为AI转型的首要领域.
- 信息学社区对于指导人工智能在放射性瘤学中的整合至关重要.
- 关键的教训强调了强大的数据实践对人工智能采用的重要性.
结论:
- 人工智能对彻底改变癌症护理,特别是辐射瘤学具有重大前景.
- 有效的数据管理和共享是成功整合AI的基础.
- 信息学界的积极准备将确保辐射瘤从人工智能技术中获益.
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