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Myths and facts about artificial intelligence: why machine- and deep-learning will not replace interventional radiologists

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Abstract

Artificial intelligence (AI) is revolutionizing healthcare and transforming the clinical practice of physicians across the world. Radiology has a strong affinity for machine learning and is at the forefront of the paradigm shift, as machines compete with humans for cognitive abilities. AI is a computer science simulation of the human mind that utilizes algorithms based on collective human knowledge and the best available evidence to process various forms of inputs and deliver desired outcomes, such as clinical diagnoses and optimal treatment options. Despite the overwhelmingly positive uptake of the technology, warnings have been published about the potential dangers of AI. Concerns have been expressed reflecting opinions that future medicine based on AI will render radiologists irrelevant. Thus, how much of this is based on reality? To answer these questions, it is important to examine the facts, clarify where AI really stands and why many of these speculations are untrue. We aim to debunk the 6 top myths regarding AI in the future of radiologists.

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Authors and Affiliations

  1. Postgraduation School in Radiodiagnostics, Università Degli Studi di Milano, Via Festa del Perdono 7, 20122, Milan, Italy

    Filippo Pesapane, Pierpaolo Biondetti & Luca Nicosia

  2. Interventional Radiology, King’s College Hospital, London, UK

    Priyan Tantrige

  3. Diagnostic and Interventional Radiology Department, San Paolo Hospital, University of Milan, Milan, Italy

    Francesca Patella

  4. UOC Radiologia, ASST Rhodense, Garbagnate Milanese, Italy

    Andrea Ianniello

  5. Department of Diagnostic Imaging, Interventional Radiology Unit, E.O. Galliera Hospital, Genova, Italy

    Umberto G. Rossi

  6. Radiology Department, Foundation IRCCS Cà Granda-Ospedale Maggiore Policlinico, Milan, Italy

    Gianpaolo Carrafiello & Anna Maria Ierardi

  7. Dipartimento Di Scienze Della Salute, Università Degli Studi di Milano, Milano, Italy

    Gianpaolo Carrafiello

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(1) Conception and design: Dr. FP, Dr. AMI. (2) Administrative support: Dr. GC, Dr. AMI. (3) Provision of study materials or patients: All Authors. (4) Collection and assembly of data: All Authors. (5) Data analysis and interpretation: All Authors. (6) Manuscript writing: All authors. (7) Final approval of manuscript: All authors.

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Pesapane, F., Tantrige, P., Patella, F. et al. Myths and facts about artificial intelligence: why machine- and deep-learning will not replace interventional radiologists. Med Oncol 37, 40 (2020). https://doi.org/10.1007/s12032-020-01368-8

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