Beyond the Artificial Intelligence Hype: What Lies Behind the Algorithms and What We Can Achieve.

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

Abstract

The field of artificial intelligence (AI) is currently experiencing a period of extensive growth in a wide variety of fields, medicine not being the exception. The base of AI is mathematics and computer science, and the current fame of AI in industry and research stands on 3 pillars: big data, high performance computing infrastructure, and algorithms. In the current digital era, increased storage capabilities and data collection systems, lead to a massive influx of data for AI algorithm. The size and quality of data are 2 major factors influencing performance of AI applications. However, it is highly dependent on the type of task at hand and algorithm chosen to perform this task. AI may potentially automate several tedious tasks in radiology, particularly in cardiothoracic imaging, by pre-readings for the detection of abnormalities, accurate quantifications, for example, oncologic volume lesion tracking and cardiac volume and image optimization. Although AI-based applications offer great opportunity to improve radiology workflow, several challenges need to be addressed starting from image standardization, sophisticated algorithm development, and large-scale evaluation. Integration of AI into the clinical workflow also needs to address legal barriers related to security and protection of patient-sensitive data and liability before AI will reach its full potential in cardiothoracic imaging.

Authors

  • Marly van Assen
    Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, Charleston, SC 29425-2260 (S.S.M., D.M., M.v.A., C.N.D.C., R.R.B., C.T., A.V.S., A.M.F., B.E.J., L.P.G., U.J.S.); Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt, Germany (S.S.M., T.J.V.); Stanford University School of Medicine, Department of Radiology, Stanford, Calif (D.M.); Division of Cardiothoracic Imaging, Nuclear Medicine and Molecular Imaging, Department of Radiology and Imaging Sciences, Emory University, Atlanta, Ga (C.N.D.C.); Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, SC (R.R.B.); Department of Cardiology and Intensive Care Medicine, Heart Center Munich-Bogenhausen, Munich, Germany (C.T.); Department of Cardiology, Munich University Clinic, Ludwig-Maximilians-University, Munich, Germany (C.T.); Siemens Medical Solutions USA, Malvern, Pa (P.S.); and Department of Emergency Medicine, Medical University of South Carolina, Charleston, SC (A.J.M.).
  • Imon Banerjee
    Mayo Clinic, Department of Radiology, Scottsdale, AZ, USA.
  • Carlo N De Cecco
    Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, Charleston, SC 29425-2260 (S.S.M., D.M., M.v.A., C.N.D.C., R.R.B., C.T., A.V.S., A.M.F., B.E.J., L.P.G., U.J.S.); Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt, Germany (S.S.M., T.J.V.); Stanford University School of Medicine, Department of Radiology, Stanford, Calif (D.M.); Division of Cardiothoracic Imaging, Nuclear Medicine and Molecular Imaging, Department of Radiology and Imaging Sciences, Emory University, Atlanta, Ga (C.N.D.C.); Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, SC (R.R.B.); Department of Cardiology and Intensive Care Medicine, Heart Center Munich-Bogenhausen, Munich, Germany (C.T.); Department of Cardiology, Munich University Clinic, Ludwig-Maximilians-University, Munich, Germany (C.T.); Siemens Medical Solutions USA, Malvern, Pa (P.S.); and Department of Emergency Medicine, Medical University of South Carolina, Charleston, SC (A.J.M.).

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