医学
软件部署
医学物理学
放射科
人工智能
软件工程
计算机科学
工程类
作者
Sirui Jiang,Syed Muhammad Awais Bukhari,Arjun Krishnan,Kaustav Bera,Avishkar Sharma,Dominique Caovan,Beverly Rosipko,Amit Gupta
摘要
Radiology, as a highly technical and information-rich medical specialty, is well-suited for artificial intelligence (AI) product development, and many FDA-cleared AI medical devices are authorized for uses within the specialty. In this Clinical Perspective, we discuss the deployment of AI tools in radiology, exploring regulatory processes, the need for transparency, and other practical challenges. We further highlight the importance of rigorous validation, real-world testing, seamless workflow integration, and end-user education. We emphasize the role for continuous feedback and robust monitoring processes, to guide AI tools' adaptation and help ensure sustained performance. Traditional standalone and alternative platform-based approaches to radiology AI implementation are considered. The presented strategies will help achieve successful deployment and fully realize AI's potential benefits in radiology.
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