Deep Learning-Assisted Diagnosis of Pediatric Skull Fractures on Plain Radiographs.

Journal: Korean journal of radiology
PMID:

Abstract

OBJECTIVE: To develop and evaluate a deep learning-based artificial intelligence (AI) model for detecting skull fractures on plain radiographs in children.

Authors

  • Jae Won Choi
  • Yeon Jin Cho
  • Ji Young Ha
    Department of Radiology, Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea.
  • Yun Young Lee
    Department of Radiology, Chonnam National University Hospital, Gwangju, Korea.
  • Seok Young Koh
    Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
  • June Young Seo
    Department of Radiology, Seoul National University Hospital, Seoul, Korea.
  • Young Hun Choi
    Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea. iater@snu.ac.kr.
  • Jung-Eun Cheon
    Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea.
  • Ji Hoon Phi
    Division of Pediatric Neurosurgery, Seoul National University Children's Hospital, Seoul, Korea.
  • Injoon Kim
    Department of Emergency Medicine, Armed Forces Yangju Hospital, Yangju, Korea.
  • Jaekwang Yang
    Army Aviation Operations Command, Icheon, Korea.
  • Woo Sun Kim
    Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea.