Artificial intelligence for imaging-based COVID-19 detection: Systematic review comparing added value of AI versus human readers.

Journal: European journal of radiology
Published Date: Nov 16, 2021

Abstract

PURPOSE: A growing number of studies have examined whether Artificial Intelligence (AI) systems can support imaging-based diagnosis of COVID-19-caused pneumonia, including both gains in diagnostic performance and speed. However, what is currently missing is a combined appreciation of studies comparing human readers and AI.

Authors

  • Christine Kriza
    European Commission, Joint Research Centre (JRC), Via E. Fermi 2749 (TP 281) Ispra, Lombardy, Italy. Electronic address: Christine.KRIZA@ec.europa.eu.
  • Valeria Amenta
    European Commission, Joint Research Centre (JRC), Via E. Fermi 2749 (TP 281) Ispra, Lombardy, Italy.
  • Alexandre Zenié
    European Commission, Joint Research Centre (JRC), Via E. Fermi 2749 (TP 281) Ispra, Lombardy, Italy.
  • Dimitris Panidis
    European Commission, Joint Research Centre (JRC), Via E. Fermi 2749 (TP 281) Ispra, Lombardy, Italy.
  • Hubert Chassaigne
    European Commission, Joint Research Centre (JRC), Via E. Fermi 2749 (TP 281) Ispra, Lombardy, Italy.
  • Patricia Urbán
    European Commission, Joint Research Centre (JRC), Via E. Fermi 2749 (TP 281) Ispra, Lombardy, Italy.
  • Uwe Holzwarth
    European Commission, Joint Research Centre (JRC), Via E. Fermi 2749 (TP 281) Ispra, Lombardy, Italy.
  • Aisha Vanessa Sauer
    European Commission, Joint Research Centre (JRC), Via E. Fermi 2749 (TP 281) Ispra, Lombardy, Italy.
  • Vittorio Reina
    European Commission, Joint Research Centre (JRC), Via E. Fermi 2749 (TP 281) Ispra, Lombardy, Italy.
  • Claudius Benedict Griesinger
    European Commission, Joint Research Centre (JRC), Via E. Fermi 2749 (TP 281) Ispra, Lombardy, Italy.

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