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Articles

Automated detection and classification of the proximal humerus fracture by using deep learning algorithm

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Pages 468-473 | Received 07 Jan 2018, Accepted 21 Feb 2018, Published online: 26 Mar 2018

  • Bengio Y, Courville A, Vincent P. Representation learning: a review and new perspectives. IEEE Trans Pattern Anal Mach Intell 2013; 35(8): 1798–828.
  • Esteva A, Kuprel B, Novoa R A, Ko J, Swetter S M, Blau H M, Thrun S. Dermatologist-level classification of skin cancer with deep neural networks. Nature 2017; 542(7639): 115–18.
  • Foroohar A, Tosti R, Richmond J M, Gaughan J P, Ilyas A M. Classification and treatment of proximal humerus fractures: inter-observer reliability and agreement across imaging modalities and experience. J Orthop Surg Res 2011; 6: 38.
  • Gulshan V, Peng L, Coram M, Stumpe M C, Wu D, Narayanaswamy A, Venugopalan S, Widner K, Madams T, Cuadros J, Kim R, Raman R, Nelson P C, Mega J L, Webster D R. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA 2016; 316(22): 2402–10.
  • Hua K L, Hsu C H, Hidayati S C, Cheng W H, Chen Y J. Computer-aided classification of lung nodules on computed tomography images via deep learning technique. Onco Targets Ther 2015; 8: 2015–22.
  • Kooi T, Litjens G, van Ginneken B, Gubern-Merida A, Sanchez C I, Mann R, den Heeten A, Karssemeijer N. Large scale deep learning for computer aided detection of mammographic lesions. Med Image Anal 2017; 35: 303–12.
  • Lakhani P, Sundaram B. Deep learning at chest radiography: automated classification of pulmonary tuberculosis by using convolutional neural networks. Radiology 2017; 284(2): 574–82.
  • LeCun Y, Bengio Y, Hinton G. Deep learning. Nature 2015; 521(7553): 436–44.
  • Mora Guix J M, Pedros J S, Serrano A C. Updated classification system for proximal humeral fractures. Clin Med Res 2009; 7(1-2): 32–44.
  • Neer C S, 2nd. Displaced proximal humeral fractures, I: Classification and evaluation. J Bone Joint Surg Am 1970; 52(6): 1077–89.
  • Olczak J, Fahlberg N, Maki A, Razavian A S, Jilert A, Stark A, Sköldenberg O, Gordon M. Artificial intelligence for analyzing orthopedic trauma radiographs. Acta Orthop 2017; 88(6): 581–6.
  • Russakovsky O, Deng J, Su H, Krause J, Satheesh S, Ma M, Huang Z, Karpathy A, Khosla A, Bernstein M, Berg A C, Fei-Fei L. ImageNet large scale visual recognition challenge. Int J Comput Vis 2015; 115(3): 211–52.
  • Shin H C, Orton M R, Collins D J, Doran S J, Leach M O. Stacked autoencoders for unsupervised feature learning and multiple organ detection in a pilot study using 4D patient data. IEEE Trans Pattern Anal Mach Intell 2013; 35(8): 1930–43.
  • Wang S, Summers R M. Machine learning and radiology. Med Image Anal 2012; 16(5): 933–51.