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. 2022 Aug;104-B(8):911-914.
doi: 10.1302/0301-620X.104B8.BJJ-2022-0119.R1.

Artificial intelligence and computer vision in orthopaedic trauma : the why, what, and how

Jasper Prijs  1   2   3 , Zhibin Liao  4 , Soheil Ashkani-Esfahani  5 , Jakub Olczak  6 , Max Gordon  6 , Prakash Jayakumar  7 , Paul C Jutte  1 , Ruurd L Jaarsma  3 , Frank F A IJpma  1 , Job N Doornberg  1   3 ; Machine Learning Consortium
Affiliations

Artificial intelligence and computer vision in orthopaedic trauma : the why, what, and how

Jasper Prijs et al. Bone Joint J. 2022 Aug.

Erratum in

  • Corrigendum.
    Prijs J, Liao Z, Ashkani-Esfahani S, Olczak J, Gordon M, Jayakumar P, Jutte PC, Jaarsma RL, IJpma FFA, Doornberg JN; Machine Learning Consortium. Prijs J, et al. Bone Joint J. 2022 Oct;104-B(10):1189. doi: 10.1302/0301-620X.104B9.BJJ-2022-00026. Bone Joint J. 2022. PMID: 36177648 No abstract available.

Abstract

Artificial intelligence (AI) is, in essence, the concept of 'computer thinking', encompassing methods that train computers to perform and learn from executing certain tasks, called machine learning, and methods to build intricate computer models that both learn and adapt, called complex neural networks. Computer vision is a function of AI by which machine learning and complex neural networks can be applied to enable computers to capture, analyze, and interpret information from clinical images and visual inputs. This annotation summarizes key considerations and future perspectives concerning computer vision, questioning the need for this technology (the 'why'), the current applications (the 'what'), and the approach to unlocking its full potential (the 'how'). Cite this article: Bone Joint J 2022;104-B(8):911-914.

Keywords: AI; Artificial intelligence; CNN; CT scans; Detection; Machine learning; clinicians; haemorrhage; medical images; orthopaedic images; orthopaedic surgery; orthopaedic trauma; postoperative infection; radiographs; trauma surgery.

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