Kottler Nina
Radiology Partners, El Segundo, California.
J Am Coll Radiol. 2020 Nov;17(11):1398-1404. doi: 10.1016/j.jacr.2020.09.029. Epub 2020 Oct 1.
Artificial intelligence (AI) is an exciting technology that can transform the practice of radiology. However, radiology AI is still immature with limited adopters, dominated by academic institutions, and few use cases in general practice. With scale and a focus on innovation, our practice has had the opportunity to be an early adopter of AI technology. We have gained experience identifying use cases that provide value for our patients and practice; selecting AI products and vendors; piloting vendors' AI algorithms; creating our own AI algorithms; implementing, optimizing, and maintaining these algorithms; garnering radiologist acceptance of these tools; and integrating AI into our radiologists' daily workflow. With this experience, our practice has both managed challenges and identified unexpected benefits of AI. To ensure a successful and scalable AI implementation, multiple steps are required, including preparing the data, systems, and radiologists. This article reviews our experience with AI and describes why each step is important.
人工智能（AI）是一项令人兴奋的技术，它可以改变放射学的实践。然而，放射学人工智能仍不成熟，采用者有限，主要由学术机构主导，在一般实践中的用例也很少。凭借规模优势和对创新的关注，我们的实践机构有机会成为人工智能技术的早期采用者。我们在识别为患者和实践带来价值的用例、选择人工智能产品和供应商、试用供应商的人工智能算法、创建我们自己的人工智能算法、实施、优化和维护这些算法、获得放射科医生对这些工具的认可，以及将人工智能整合到我们放射科医生的日常工作流程等方面积累了经验。有了这些经验，我们的实践机构既应对了挑战，也发现了人工智能带来的意外好处。为确保人工智能的成功实施和可扩展性，需要采取多个步骤，包括准备数据、系统和放射科医生。本文回顾了我们在人工智能方面的经验，并描述了每个步骤为何重要。
