Department of Biomedical Data Science, Stanford University, 1265 Welch Rd, Stanford, CA 94305, USA.
Radiol Clin North Am. 2021 Nov;59(6):1063-1074. doi: 10.1016/j.rcl.2021.07.006.
Although recent scientific studies suggest that artificial intelligence (AI) could provide value in many radiology applications, much of the hard engineering work required to consistently realize this value in practice remains to be done. In this article, we summarize the various ways in which AI can benefit radiology practice, identify key challenges that must be overcome for those benefits to be delivered, and discuss promising avenues by which these challenges can be addressed.
虽然最近的科学研究表明人工智能（AI）可以在许多放射学应用中提供价值，但要在实践中始终实现这一价值，仍需要完成大量的艰苦工程工作。在本文中，我们总结了 AI 可以使放射学实践受益的各种方式，确定了必须克服的关键挑战，以实现这些好处，并讨论了可以解决这些挑战的有前途的途径。
