Malpani Rohil, Petty Christopher W, Bhatt Neha, Staib Lawrence H, Chapiro Julius
Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 330 Cedar Street, New Haven, CT 06520, USA.
Dig Dis Interv. 2021;5(4):331-337. doi: 10.1055/s-0041-1726300. Epub 2021 Jul 17.
The future of radiology is disproportionately linked to the applications of artificial intelligence (AI). Recent exponential advancements in AI are already beginning to augment the clinical practice of radiology. Driven by a paucity of review articles in the area, this article aims to discuss applications of AI in non-oncologic IR across procedural planning, execution, and follow-up along with a discussion on the future directions of the field. Applications in vascular imaging, radiomics, touchless software interactions, robotics, natural language processing, post-procedural outcome prediction, device navigation, and image acquisition are included. Familiarity with AI study analysis will help open the current 'black box' of AI research and help bridge the gap between the research laboratory and clinical practice.
放射学的未来与人工智能（AI）的应用有着极其紧密的联系。近期人工智能呈指数级的进展已开始提升放射学的临床实践。鉴于该领域综述文章匮乏，本文旨在探讨人工智能在非肿瘤介入放射学中在程序规划、执行和随访方面的应用，并讨论该领域的未来发展方向。内容包括血管成像、影像组学、非接触式软件交互、机器人技术、自然语言处理、术后结果预测、设备导航及图像采集等方面的应用。熟悉人工智能研究分析将有助于打开当前人工智能研究的“黑匣子”，并有助于弥合研究实验室与临床实践之间的差距。
