Predicting Perceived Reporting Complexity of Abdominopelvic Computed Tomography With Deep Learning.

Journal: Journal of computer assisted tomography
Published Date: May 18, 2022

Abstract

OBJECTIVE: The purpose of this pilot study was to examine human and automated estimates of reporting complexity for computed tomography (CT) studies of the abdomen and pelvis.

Authors

  • Phillip M Cheng
    From the Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA.
  • Gilbert Whang
    Department of Radiology, USC Norris Comprehensive Cancer Center, Keck School of Medicine of USC, 1441 Eastlake Avenue, Suite 2315B, Los Angeles, CA, 90033-0377, USA.
  • Evan Allgood
  • Tapas K Tejura
    Department of Radiology, USC Norris Comprehensive Cancer Center, Keck School of Medicine of USC, 1441 Eastlake Avenue, Suite 2315B, Los Angeles, CA, 90033-0377, USA.

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