Department of Diagnostic Radiology, Changi General Hospital, Singapore.
Ann Acad Med Singap. 2019 Jan;48(1):16-24.
Artificial intelligence (AI) has been positioned as being the most important recent advancement in radiology, if not the most potentially disruptive. Singapore radiologists have been quick to embrace this technology as part of the natural progression of the discipline toward a vision of how clinical medicine, empowered by technology, can achieve our national healthcare objectives of delivering value-based and patient-centric care. In this article, we consider 3 core questions relating to AI in radiology, and review the barriers to the widespread adoption of AI in radiology. We propose solutions and describe a "Centaur" model as a promising avenue for enabling the interfacing between AI and radiologists. Finally, we introduce The Radiological AI, Data Science and Imaging Informatics (RADII) subsection of the Singapore Radiological Society. RADII is an enabling body, which together with key technological and institutional stakeholders, will champion research, development and evaluation of AI for radiology applications.
人工智能(AI)被认为是放射学领域最近最重要的进展,如果不是最具颠覆性的话。新加坡放射科医生很快就接受了这项技术,将其视为该学科向临床实践的自然发展,借助技术实现我们国家医疗保健目标,提供以价值为基础和以患者为中心的护理。在本文中,我们考虑了与放射学中的 AI 相关的 3 个核心问题,并回顾了 AI 在放射学中广泛采用的障碍。我们提出了解决方案,并描述了“半人马”模型作为在 AI 和放射科医生之间实现接口的有前途的途径。最后,我们介绍了新加坡放射学会的放射学人工智能、数据科学和成像信息学(RADII)小组。RADII 是一个支持机构,它将与关键的技术和机构利益相关者一起,倡导用于放射学应用的 AI 的研究、开发和评估。