The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, 601 North Caroline Street, JHOC 3262, Baltimore, MD, 21287, USA.
The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, 600 North Wolfe Street, Hal B168, Baltimore, MD, 21287, USA.
Emerg Radiol. 2020 Aug;27(4):361-366. doi: 10.1007/s10140-020-01773-6. Epub 2020 Jul 8.
Predictions related to the impact of AI on radiology as a profession run the gamut from AI putting radiologists out of business to having no effect at all. The use of AI appears to show significant promise in ER triage in the present. We briefly discuss the emerging effectiveness of AI in the ER imaging setting by looking at some of the products approved by the FDA and finding their way into "practice." The FDA approval process to date has focused on applications that affect patient triage and not necessarily ones that have the computer serve as the only or final reader. We describe a select group of applications to provide the reader with a sense of the current state of AI use in the ER setting to assess neurologic, pulmonary, and musculoskeletal trauma indications. In the process, we highlight the benefits of triage staging using AI, such as accelerating diagnosis and optimizing workflow, with few downsides. The ability to triage patients and take care of acute processes such as intracranial bleed, pneumothorax, and pulmonary embolism will largely benefit the health system, improving patient care and reducing costs. These capabilities are all available now. This first wave of AI applications is not replacing radiologists. Rather, the innovative software is improving throughput, contributing to the timeliness in which radiologists can get to read abnormal scans, and possibly enhances radiologists' accuracy. As for what the future holds for the use of AI in radiology, only time will tell.
关于人工智能对放射科职业影响的预测，从人工智能使放射科医生失业到人工智能根本没有影响，可谓众说纷纭。目前，人工智能在急诊分诊中似乎显示出了巨大的应用潜力。我们简要讨论了人工智能在急诊成像环境中的新兴有效性，研究了一些获得美国食品和药物管理局 (FDA) 批准并在“实践”中应用的产品。迄今为止，FDA 的审批程序主要集中在影响患者分诊的应用程序上，而不一定是让计算机作为唯一或最终的读片者。我们描述了一组精选的应用程序，让读者了解人工智能在急诊环境中的当前应用状态，以评估神经、肺部和肌肉骨骼创伤的适应症。在此过程中，我们强调了使用人工智能进行分诊分期的好处，例如加速诊断和优化工作流程，而几乎没有缺点。分诊患者和处理急性疾病（如颅内出血、气胸和肺栓塞）的能力将使医疗系统受益匪浅，改善患者护理并降低成本。这些功能现在都已经具备了。这第一波人工智能应用不会取代放射科医生。相反，创新软件提高了工作效率，有助于放射科医生及时阅读异常扫描，并可能提高放射科医生的准确性。至于人工智能在放射科中的未来应用前景如何，只有时间才能证明。
