Artificial intelligence in orthopaedics: A scoping review

There is a growing interest in the application of artificial intelligence (AI) to orthopaedic surgery. This review aims to identify and characterise research in this field, in order to understand the extent, range and nature of this work, and act as springboard to stimulate future studies. A scoping...

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Bibliographic Details
Published in:PloS one 2021-11, Vol.16 (11), p.e0260471-e0260471
Main Authors: Federer, Simon J, Jones, Gareth G
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Biology and Life Sciences
Clinical Decision-Making - methods
Clinical medicine
Computer and Information Sciences
Datasets
Decision Making, Computer-Assisted
Deep learning
Fractures
Humans
Image Processing, Computer-Assisted - methods
Innovations
Joint surgery
Machine learning
Medicine and Health Sciences
Methods
Orthopedic Procedures - methods
Orthopedics
Patients
Physical Sciences
Research and Analysis Methods
Reviews
Spine
Technology application
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Summary:There is a growing interest in the application of artificial intelligence (AI) to orthopaedic surgery. This review aims to identify and characterise research in this field, in order to understand the extent, range and nature of this work, and act as springboard to stimulate future studies. A scoping review, a form of structured evidence synthesis, was conducted to summarise the use of AI in orthopaedics. A literature search (1946-2019) identified 222 studies eligible for inclusion. These studies were predominantly small and retrospective. There has been significant growth in the number of papers published in the last three years, mainly from the USA (37%). The majority of research used AI for image interpretation (45%) or as a clinical decision tool (25%). Spine (43%), knee (23%) and hip (14%) were the regions of the body most commonly studied. The application of artificial intelligence to orthopaedics is growing. However, the scope of its use so far remains limited, both in terms of its possible clinical applications, and the sub-specialty areas of the body which have been studied. A standardized method of reporting AI studies would allow direct assessment and comparison. Prospective studies are required to validate AI tools for clinical use.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0260471