Evaluation of the models generated from clinical features and deep learning-based segmentations: Can thoracic CT on admission help us to predict hospitalized COVID-19 patients who will require intensive care?

Journal: BMC medical imaging
Published Date: Jun 7, 2022

Abstract

BACKGROUND: The aim of the study was to predict the probability of intensive care unit (ICU) care for inpatient COVID-19 cases using clinical and artificial intelligence segmentation-based volumetric and CT-radiomics parameters on admission.

Authors

  • Mutlu Gülbay
    Department of Radiology, Ankara City Hospital, Üniversiteler Mahallesi 1604. Cadde No: 9, 06800, Çankaya, Ankara, Turkey. drgulbay@gmail.com.
  • Aliye Baştuğ
    Department of Infectious Diseases and Clinical Microbiology, University of Health Sciences Turkey, Gülhane Faculty of Medicine, Ankara City Hospital, Ankara, Turkey.
  • Erdem Özkan
    Department of Radiology, Ankara City Hospital, Üniversiteler Mahallesi 1604. Cadde No: 9, 06800, Çankaya, Ankara, Turkey.
  • Büşra Yüce Öztürk
    Department of Clinical Microbiology and Infectious Diseases, Ankara City Hospital, Ankara, Turkey.
  • Bökebatur Ahmet Raşit Mendi
    Department of Radiology, Ankara City Hospital, Üniversiteler Mahallesi 1604. Cadde No: 9, 06800, Çankaya, Ankara, Turkey.
  • Hürrem Bodur
    Department of Infectious Diseases and Clinical Microbiology, University of Health Sciences Turkey, Gülhane Faculty of Medicine, Ankara City Hospital, Ankara, Turkey.

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