Artificial Intelligence Pertaining to Cardiothoracic Imaging and Patient Care: Beyond Image Interpretation.

Journal: Journal of thoracic imaging
Published Date: May 1, 2020

Abstract

Artificial intelligence (AI) is a broad field of computational science that includes many subsets. Today the most widely used subset in medical imaging is machine learning (ML). Many articles have focused on the use of ML for pattern recognition to detect and potentially diagnose various pathologies. However, AI algorithm development is now directed toward workflow management. AI can impact patient care at multiple stages of their imaging experience and assist in efficient and effective scheduling, imaging performance, worklist prioritization, image interpretation, and quality assurance. The purpose of this manuscript was to review the potential AI applications in radiology focusing on workflow management and discuss how ML will affect cardiothoracic imaging.

Authors

  • William Moore
    Department of Radiology (M.K., W.M., K.F., J.S.B., G.M., J.P.K.), Department of Medicine, Division of Hematology and Medical Oncology, Laura and Isaac Perlmutter Cancer Center (D.K.), and Center for Healthcare Innovation and Delivery Science (L.I.H.), NYU Langone Health, 550 First Ave, New York, NY 10016; Division of Healthcare Delivery Science, Department of Population Health and Division of General Internal Medicine and Clinical Innovation, Department of Medicine, NYU Grossman School of Medicine, New York, NY (L.I.H.); and Garden State Urology, Wayne, NJ (A.K.).
  • Jane Ko
  • Elliott Gozansky

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