• Ann Acad Med Singap · Jan 2019

    Review

    Artificial Intelligence and Radiology in Singapore: Championing a New Age of Augmented Imaging for Unsurpassed Patient Care.

    • Charlene Jy Liew, Pavitra Krishnaswamy, Lionel Te Cheng, Cher Heng Tan, Angeline Cc Poh, and Tchoyoson Cc Lim.
    • Department of Diagnostic Radiology, Changi General Hospital, Singapore.
    • Ann Acad Med Singap. 2019 Jan 1; 48 (1): 16-24.

    AbstractArtificial 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.

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