Systematic review of artificial intelligence tack in preventive orthopaedics: is the land coming soon?

Systematic review of artificial intelligence tack in preventive orthopaedics: is the land coming soon?

Purpose This study aims to describe and assess the current stage of the artificial intelligence (AI) technology integration in preventive orthopaedics of the knee and hip joints. Materials and methods The study was conducted in strict compliance with the Preferred Reporting Items for Systematic Revi...

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Bibliographic Details
Published in:International orthopaedics Vol. 47; no. 2; pp. 393 - 403
Main Authors: Korneev, Alexander, Lipina, Marina, Lychagin, Alexey, Timashev, Peter, Kon, Elizaveta, Telyshev, Dmitry, Goncharuk, Yuliya, Vyazankin, Ivan, Elizarov, Mikhail, Murdalov, Emirkhan, Pogosyan, David, Zhidkov, Sergei, Bindeeva, Anastasia, Liang, Xing-Jie, Lasovskiy, Vladimir, Grinin, Victor, Anosov, Alexey, Kalinsky, Eugene
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-02-2023
Subjects:
Artificial Intelligence
Hip Joint
Humans
Medicine
Medicine & Public Health
Orthopedic Procedures
Orthopedics
Review
Software
Hip joint
Knee joint
MRI
X-rays
Lower limb
Artificial intelligence
Osteoarthritis
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Summary:Purpose This study aims to describe and assess the current stage of the artificial intelligence (AI) technology integration in preventive orthopaedics of the knee and hip joints. Materials and methods The study was conducted in strict compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. Literature databases were searched for articles describing the development and validation of AI models aimed at diagnosing knee or hip joint pathologies or predicting their development or course in patients. The quality of the included articles was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and QUADAS-AI tools. Results 56 articles were found that meet all the inclusion criteria. We identified two problems that block the full integration of AI into the routine of an orthopaedic physician. The first of them is related to the insufficient amount, variety and quality of data for training, and validation and testing of AI models. The second problem is the rarity of rational evaluation of models, which is why their real quality cannot always be evaluated. Conclusion The vastness and relevance of the studied topic are beyond doubt. Qualitative and optimally validated models exist in all four scopes considered. Additional optimization and confirmation of the models’ quality on various datasets are the last technical stumbling blocks for creating usable software and integrating them into the routine of an orthopaedic physician.
Bibliography:ObjectType-Article-2
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ISSN:0341-2695
1432-5195
DOI:10.1007/s00264-022-05628-2