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. 2022 Aug 26:34:201-206.
doi: 10.1016/j.jor.2022.08.020. eCollection 2022 Nov-Dec.

Current understanding on artificial intelligence and machine learning in orthopaedics - A scoping review

Vishal Kumar  1 , Sandeep Patel  1 , Vishnu Baburaj  1 , Aditya Vardhan  1 , Prasoon Kumar Singh  1 , Raju Vaishya  2
Affiliations

Current understanding on artificial intelligence and machine learning in orthopaedics - A scoping review

Vishal Kumar et al. J Orthop. .

Abstract

Background: Artificial Intelligence (AI) has improved the way of looking at technological challenges. Today, we can afford to see many of the problems as just an input-output system rather than solving from the first principles. The field of Orthopaedics is not spared from this rapidly expanding technology. The recent surge in the use of AI can be attributed mainly to advancements in deep learning methodologies and computing resources. This review was conducted to draw an outline on the role of AI in orthopaedics.

Methods: We developed a search strategy and looked for articles on PubMed, Scopus, and EMBASE. A total of 40 articles were selected for this study, from tools for medical aid like imaging solutions, implant management, and robotic surgery to understanding scientific questions.

Results: A total of 40 studies have been included in this review. The role of AI in the various subspecialties such as arthroplasty, trauma, orthopaedic oncology, foot and ankle etc. have been discussed in detail.

Conclusion: AI has touched most of the aspects of Orthopaedics. The increase in technological literacy, data management plans, and hardware systems, amalgamated with the access to hand-held devices like mobiles, and electronic pads, augur well for the exciting times ahead in this field. We have discussed various technological breakthroughs in AI that have been able to perform in Orthopaedics, and also the limitations and the problem with the black-box approach of modern AI algorithms. We advocate for better interpretable algorithms which can help both the patients and surgeons alike.

Keywords: Arthroplasty; Artificial intelligence; Deep learning; Machine learning; Orthopaedics; Trauma.

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Conflict of interest statement

None.

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PRISMA Flowchart.
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