AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset.

Journal: European radiology
Published Date: Jun 4, 2021

Abstract

OBJECTIVE: Assess if deep learning-based artificial intelligence (AI) algorithm improves reader performance for lung cancer detection on chest X-rays (CXRs).

Authors

  • Hyunsuk Yoo
    Lunit, Seoul, South Korea.
  • Sang Hyup Lee
    Department of Urology, Kyung Hee University School of Medicine, Seoul, Korea.
  • Chiara Daniela Arru
  • Ruhani Doda Khera
    Division of Thoracic Imaging, Department of Radiology, Massachusetts General Hospital, 75 Blossom Court, Boston, MA, 02114, USA.
  • Ramandeep Singh
    Massachusetts General Hospital, Department of Radiolgoy, United States.
  • Sean Siebert
    Division of Thoracic Imaging, Department of Radiology, Massachusetts General Hospital, 75 Blossom Court, Boston, MA, 02114, USA.
  • Dohoon Kim
    Department of Molecular, Cell and Cancer Biology, University of Massachusetts Medical School, Worcester, MA, 01655, USA.
  • Yuna Lee
    Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.
  • Ju Hyun Park
    Suwon Total Healthcare Center, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Youngin-si, Gyeongi-do, 16954, Korea.
  • Hye Joung Eom
    Cheju Halla General Hospital, 65 Doryeong-ro, Yeon-dong, Jeju-si, Jeju-do, Korea.
  • Subba R Digumarthy
    Massachusetts General Hospital, Department of Radiolgoy, United States.
  • Mannudeep K Kalra

Keywords

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