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Acta Orthopaedica Volume 92, 2021 - Issue 1
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Articles

Ankle fracture classification using deep learning: automating detailed AO Foundation/Orthopedic Trauma Association (AO/OTA) 2018 malleolar fracture identification reaches a high degree of correct classification

Jakub OlczakKarolinska Institute, Institution for Clinical Sciences, Danderyd University Hospital, Stockholm, SwedenCorrespondence[email protected]
,
Filip EmilsonKarolinska Institute, Institution for Clinical Sciences, Danderyd University Hospital, Stockholm, Sweden
,
Ali RazavianKarolinska Institute, Institution for Clinical Sciences, Danderyd University Hospital, Stockholm, Sweden
,
Tone AntonssonKarolinska Institute, Institution for Clinical Sciences, Danderyd University Hospital, Stockholm, Sweden
,
Andreas StarkKarolinska Institute, Institution for Clinical Sciences, Danderyd University Hospital, Stockholm, Sweden
&
Max GordonKarolinska Institute, Institution for Clinical Sciences, Danderyd University Hospital, Stockholm, Sweden
Pages 102-108 | Published online: 26 Oct 2020

  • Albert . Multivariate interpretation of clinical laboratory data. Boca Raton, FL: CRC Press; 1987.
  • Aoki K , Misumi J , Kimura T , Zhao W , Xie T . Evaluation of cutoff levels for screening of gastric cancer using serum pepsinogens and distributions of levels of serum pepsinogen I, II and of PG I/PG II ratios in a gastric cancer case-control study. J Epidemiol 1997; 7(3): 143–51.
  • Association Committee for Coding and Classification. Fracture and dislocation compendium . Orthopaedic Trauma Association Committee for Coding and Classification. J Orthop Trauma 1996; 10(Suppl. 1): v-ix, 1–154.
  • Budny A M , Young B A . Analysis of radiographic classifications for rotational ankle fractures. Clin Podiatr Med Surg 2008; 25(2): 139–52.
  • Cabitza F , Locoro A , Banfi G . Machine learning in orthopedics: a literature review. Front Bioeng Biotechnol [Internet] 2018 Jun 27 [cited 2019 Oct 29]; 6. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030383/
  • Chung S W , Han S S , Lee J W , Oh K-S , Kim N R , Yoon J P , et al. Automated detection and classification of the proximal humerus fracture by using deep learning algorithm. Acta Orthop 2018; 89(4): 468–73.
  • Delgado R , Tibau X-A . Why Cohen’s Kappa should be avoided as performance measure in classification. PLOS ONE 2019; 14(9): e0222916.
  • Esteva A , Kuprel B , Novoa R A , Ko J , Swetter S M , Blau H M , et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature 2017; 542(7639): 115.
  • Fonseca L , Nunes I , Nogueira R , Martins G , Mesencio A , Kobata S . Reproducibility of the Lauge-Hansen, Danis–Weber, and AO classifications for ankle fractures. Rev Bras Ortop Engl Ed 2017; Dec 1: 53.
  • Gan K , Xu D , Lin Y , Shen Y , Zhang T , Hu K , et al. Artificial intelligence detection of distal radius fractures: a comparison between the convolutional neural network and professional assessments. Acta Orthop 2019; 90(4): 394–400.
  • Greiner M , Pfeiffer D , Smith R D . Principles and practical application of the receiver-operating characteristic analysis for diagnostic tests. Prev Vet Med 2000; 45(1): 23–41.
  • Guillaumin M , Verbeek J , Schmid C . Multimodal semi-supervised learning for image classification. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition [Internet]. San Francisco, CA: IEEE; 2010 [cited 2020 Jan 14]. p. 902–9. Available from: http://ieeexplore.ieee.org/document/5540120/
  • Hansen N L . Ankelbrud i genetisk Diagnose og Reposition: experimental-chirurgiske og radiografiske Undersøgelser Repositionsforsøg i Kliniken. Copenhagen: E. Munksgaard; 1942.
  • He K , Zhang X , Ren S , Sun J . Delving deep into rectifiers: surpassing human-level performance on ImageNet Classification. 2015 [cited 2016 Aug 19]. p. 1026–34. Available from: http://www.cv-foundation.org/openaccess/content_iccv_2015/html/He_Delving_Deep_into_ICCV_2015_paper.html
  • Hughes J L , Weber H , Willenegger H , Kuner E H . Evaluation of ankle fractures: non-operative and operative treatment. Clin Orthop Relat Res 1979; (138): 111.
  • Izmailov P , Podoprikhin D , Garipov T , Vetrov D , Wilson A G . Averaging weights leads to wider optima and better generalization. ArXiv180305407 Cs Stat [Internet] 2019 Feb 25 [cited 2019 Nov 16]. Available from: http://arxiv.org/abs/1803.05407
  • Juto H , Nilsson H , Morberg P . Epidemiology of adult ankle fractures: 1756 cases identified in Norrbotten County during 2009–2013 and classified according to AO/OTA. BMC Musculoskelet Disord 2018; 19(1): 441.
  • Kim D H , MacKinnon T . Artificial intelligence in fracture detection: transfer learning from deep convolutional neural networks. Clin Radiol 2018; 73(5): 439–45.
  • Lee J-G , Jun S , Cho Y-W , Lee H , Kim GB , Seo JB , et al. Deep Learning in Medical Imaging: General Overview. Korean J Radiol 2017; 18(4): 570–84.
  • Meinberg E G , Agel J , Roberts C S , Karam M D , Kellam J F . Fracture and dislocation classification compendium—2018. J Orthop Trauma 2018; 32(Suppl. 1): S1–S170.
  • Olczak J , Fahlberg N , Maki A , Razavian A S , Jilert A , Stark A , et al. Artificial intelligence for analyzing orthopedic trauma radiographs. Acta Orthop 2017; 88(6): 581–6.
  • Shapiro D E . The interpretation of diagnostic tests. Stat Methods Med Res 1999; 8(2): 113–34.
  • Thur C K , Edgren G , Jansson K-Å , Wretenberg P . Epidemiology of adult ankle fractures in Sweden between 1987 and 2004. Acta Orthop 2012; 83(3): 276–81.
  • Urakawa T , Tanaka Y , Goto S , Matsuzawa H , Watanabe K , Endo N . Detecting intertrochanteric hip fractures with orthopedist-level accuracy using a deep convolutional neural network. Skeletal Radiol 2019; 48(2): 239–44.
  • Westerman R W , Porter K . Ankle fractures in adults: an overview. Trauma 2007; 9(4): 267–72.
  • Youden W J . Index for rating diagnostic tests. Cancer 1950; 3(1): 32–5.
  • Zweig M H , Campbell G . Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinic medicine. Clin Chem 1993; 39(4): 561–77.

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