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机器智能在辐射科学中的应用:第 67 届放射研究学会年会研讨会综述。

Machine intelligence for radiation science: summary of the Radiation Research Society 67th annual meeting symposium.

机构信息

Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA.

Department of Anesthesia and Critical Care Medicine, The Children's Hospital of Philadelphia Research Institute, Philadelphia, PA, USA.

出版信息

Int J Radiat Biol. 2023;99(8):1291-1300. doi: 10.1080/09553002.2023.2173823. Epub 2023 Feb 6.

Abstract

The era of high-throughput techniques created big data in the medical field and research disciplines. Machine intelligence (MI) approaches can overcome critical limitations on how those large-scale data sets are processed, analyzed, and interpreted. The 67 Annual Meeting of the Radiation Research Society featured a symposium on MI approaches to highlight recent advancements in the radiation sciences and their clinical applications. This article summarizes three of those presentations regarding recent developments for metadata processing and ontological formalization, data mining for radiation outcomes in pediatric oncology, and imaging in lung cancer.

摘要

高通量技术时代在医学领域和研究学科中创造了大数据。机器智能(MI)方法可以克服处理、分析和解释这些大规模数据集的关键限制。放射研究学会第 67 届年会的一个专题研讨会以 MI 方法为特色,重点介绍了放射科学及其临床应用的最新进展。本文总结了其中三个演讲,内容涉及元数据处理和本体形式化、儿科肿瘤放射治疗结果的数据挖掘以及肺癌成像的最新进展。

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