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Review
. 2022 Dec 15:4:995526.
doi: 10.3389/fmedt.2022.995526. eCollection 2022.

Applications of artificial intelligence in orthopaedic surgery

Faraz Farhadi  1   2 , Matthew R Barnes  1 , Harun R Sugito  1 , Jessica M Sin  3 , Eric R Henderson  4 , Joshua J Levy  5
Affiliations
Review

Applications of artificial intelligence in orthopaedic surgery

Faraz Farhadi et al. Front Med Technol. .

Abstract

The practice of medicine is rapidly transforming as a result of technological breakthroughs. Artificial intelligence (AI) systems are becoming more and more relevant in medicine and orthopaedic surgery as a result of the nearly exponential growth in computer processing power, cloud based computing, and development, and refining of medical-task specific software algorithms. Because of the extensive role of technologies such as medical imaging that bring high sensitivity, specificity, and positive/negative prognostic value to management of orthopaedic disorders, the field is particularly ripe for the application of machine-based integration of imaging studies, among other applications. Through this review, we seek to promote awareness in the orthopaedics community of the current accomplishments and projected uses of AI and ML as described in the literature. We summarize the current state of the art in the use of ML and AI in five key orthopaedic disciplines: joint reconstruction, spine, orthopaedic oncology, trauma, and sports medicine.

Keywords: Orthopaedic Surgery; Orthopaedics; artificial intelligence; deep learning; machine learning.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Evolution of the number of total publications and citations whose title, abstract and/or keywords refer to the field of artificial intelligence in orthopaedics during the last years. Data retrieved from Web-of-science (June 20th, 2022) by using the search term: orthopaedic* AND (Artificial Intelligence OR Deep Learning OR Machine Learning OR Convolutional Neural Network).
Figure 2
Figure 2
Illustrating the key disciplines of artificial intelligence (AI), including machine learning (ML) approaches that are influencing orthopaedics research.
Figure 3
Figure 3
Common applications of AI in orthopaedics.
See this image and copyright information in PMC

References

    1. Toosi A, Bottino AG, Saboury B, Siegel E, Rahmim A. A brief history of AI: how to prevent another winter (A critical review). PET Clin. (2021) 16(4):449–69. 10.1016/j.cpet.2021.07.001 - DOI - PubMed
    1. A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence (1955). 34 p.
    1. Khan AA, Laghari AA, Awan SA. Machine learning in computer vision: a review. EAI Endorsed Scal Inf Syst. (2021) 8(32):e4. 10.4108/eai.21-4-2021.169418 - DOI
    1. Raza K, Singh NK. A Tour of Unsupervised Deep Learning for Medical Image Analysis. arXiv [eess.IV]. (2018). Available at: http://arxiv.org/abs/1812.07715 - PubMed
    1. Zhang Y, Jordan JM. Epidemiology of osteoarthritis. Clin Geriatr Med. (2010) 26(3):355–69. 10.1016/j.cger.2010.03.001 - DOI - PMC - PubMed

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