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Optimizing Radiologic Detection of COVID-19

Test Set Technologies and Artificial Intelligence

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Artificial Intelligence in Medicine

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Abstract

COVID-19 has had a huge impact globally. This chapter examines the role that test set technologies coupled with artificial intelligence can transform clinical educational strategies. Using AI to streamline a methodology that has been around for decades enables education that is tailored to each clinician, acknowledges each individual’s weaknesses, and is available instantly wherever in the world the clinician is available. Cautionary notes are also provided.

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Authors and Affiliations

  1. University of Sydney, Sydney, NSW, Australia

    Z. Gandomkar, P. C. Brennan & M. E. Suleiman

Authors
  1. Z. Gandomkar
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  2. P. C. Brennan
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  3. M. E. Suleiman
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Corresponding author

Correspondence to P. C. Brennan .

Editor information

Editors and Affiliations

  1. Department of Women’s and Children’s Health, Karolinska Institutet, Stockholm, Sweden

    Niklas Lidströmer

  2. Imperial College London, London, UK

    Hutan Ashrafian

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Gandomkar, Z., Brennan, P.C., Suleiman, M.E. (2022). Optimizing Radiologic Detection of COVID-19. In: Lidströmer, N., Ashrafian, H. (eds) Artificial Intelligence in Medicine. Springer, Cham. https://doi.org/10.1007/978-3-030-64573-1_285

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  • DOI: https://doi.org/10.1007/978-3-030-64573-1_285

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-64572-4

  • Online ISBN: 978-3-030-64573-1

  • eBook Packages: MedicineReference Module Medicine

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