@article{6953b0eb0c6d4387bfe40f94b3ff865d,
title = "Deep learning evaluation of pelvic radiographs for position, hardware presence, and fracture detection",
keywords = "Artificial intelligence, Deep learning, Fracture, Machine learning, Radiographs, Area Under Curve, Humans, Male, Pelvis/diagnostic imaging, Deep Learning, Radiography/methods, Internal Fixators, Fractures, Bone/diagnostic imaging, Female, ROC Curve, Aged, Retrospective Studies, Radiographic Image Interpretation, Computer-Assisted/methods",
author = "Gene Kitamura",
note = "Copyright {\textcopyright} 2020 Elsevier B.V. All rights reserved.",
year = "2020",
month = sep,
doi = "10.1016/j.ejrad.2020.109139",
language = "English",
volume = "130",
journal = "European Journal of Radiology",
issn = "0720-048X",
}