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Artificial intelligence in orthopaedic surgery: exploring its applications, limitations, and future direction

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient...

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Detalles Bibliográficos
Autores principales: Lisacek-Kiosoglous, Anthony B., Powling, Amber S., Fontalis, Andreas, Gabr, Ayman, Mazomenos, Evangelos, Haddad, Fares S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The British Editorial Society of Bone & Joint Surgery 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329876/
https://www.ncbi.nlm.nih.gov/pubmed/37423607
http://dx.doi.org/10.1302/2046-3758.127.BJR-2023-0111.R1
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author Lisacek-Kiosoglous, Anthony B.
Powling, Amber S.
Fontalis, Andreas
Gabr, Ayman
Mazomenos, Evangelos
Haddad, Fares S.
author_facet Lisacek-Kiosoglous, Anthony B.
Powling, Amber S.
Fontalis, Andreas
Gabr, Ayman
Mazomenos, Evangelos
Haddad, Fares S.
author_sort Lisacek-Kiosoglous, Anthony B.
collection PubMed
description The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction. Cite this article: Bone Joint Res 2023;12(7):447–454.
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spelling pubmed-103298762023-07-10 Artificial intelligence in orthopaedic surgery: exploring its applications, limitations, and future direction Lisacek-Kiosoglous, Anthony B. Powling, Amber S. Fontalis, Andreas Gabr, Ayman Mazomenos, Evangelos Haddad, Fares S. Bone Joint Res Other The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction. Cite this article: Bone Joint Res 2023;12(7):447–454. The British Editorial Society of Bone & Joint Surgery 2023-07-10 /pmc/articles/PMC10329876/ /pubmed/37423607 http://dx.doi.org/10.1302/2046-3758.127.BJR-2023-0111.R1 Text en © 2023 Author(s) et al. https://creativecommons.org/licenses/by-nc-nd/4.0/https://online.boneandjoint.org.uk/TDMThis is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (CC BY-NC-ND 4.0) licence, which permits the copying and redistribution of the work only, and provided the original author and source are credited. See https://creativecommons.org/licenses/by-nc-nd/4.0/
spellingShingle Other
Lisacek-Kiosoglous, Anthony B.
Powling, Amber S.
Fontalis, Andreas
Gabr, Ayman
Mazomenos, Evangelos
Haddad, Fares S.
Artificial intelligence in orthopaedic surgery: exploring its applications, limitations, and future direction
title Artificial intelligence in orthopaedic surgery: exploring its applications, limitations, and future direction
title_full Artificial intelligence in orthopaedic surgery: exploring its applications, limitations, and future direction
title_fullStr Artificial intelligence in orthopaedic surgery: exploring its applications, limitations, and future direction
title_full_unstemmed Artificial intelligence in orthopaedic surgery: exploring its applications, limitations, and future direction
title_short Artificial intelligence in orthopaedic surgery: exploring its applications, limitations, and future direction
title_sort artificial intelligence in orthopaedic surgery: exploring its applications, limitations, and future direction
topic Other
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329876/
https://www.ncbi.nlm.nih.gov/pubmed/37423607
http://dx.doi.org/10.1302/2046-3758.127.BJR-2023-0111.R1
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