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Machine learning in orthopaedic surgery
Artificial intelligence and machine learning in orthopaedic surgery has gained mass interest over the last decade or so. In prior studies, researchers have demonstrated that machine learning in orthopaedics can be used for different applications such as fracture detection, bone tumor diagnosis, dete...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8472446/ https://www.ncbi.nlm.nih.gov/pubmed/34631452 http://dx.doi.org/10.5312/wjo.v12.i9.685 |
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author | Lalehzarian, Simon P Gowd, Anirudh K Liu, Joseph N |
author_facet | Lalehzarian, Simon P Gowd, Anirudh K Liu, Joseph N |
author_sort | Lalehzarian, Simon P |
collection | PubMed |
description | Artificial intelligence and machine learning in orthopaedic surgery has gained mass interest over the last decade or so. In prior studies, researchers have demonstrated that machine learning in orthopaedics can be used for different applications such as fracture detection, bone tumor diagnosis, detecting hip implant mechanical loosening, and grading osteoarthritis. As time goes on, the utility of artificial intelligence and machine learning algorithms, such as deep learning, continues to grow and expand in orthopaedic surgery. The purpose of this review is to provide an understanding of the concepts of machine learning and a background of current and future orthopaedic applications of machine learning in risk assessment, outcomes assessment, imaging, and basic science fields. In most cases, machine learning has proven to be just as effective, if not more effective, than prior methods such as logistic regression in assessment and prediction. With the help of deep learning algorithms, such as artificial neural networks and convolutional neural networks, artificial intelligence in orthopaedics has been able to improve diagnostic accuracy and speed, flag the most critical and urgent patients for immediate attention, reduce the amount of human error, reduce the strain on medical professionals, and improve care. Because machine learning has shown diagnostic and prognostic uses in orthopaedic surgery, physicians should continue to research these techniques and be trained to use these methods effectively in order to improve orthopaedic treatment. |
format | Online Article Text |
id | pubmed-8472446 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-84724462021-10-07 Machine learning in orthopaedic surgery Lalehzarian, Simon P Gowd, Anirudh K Liu, Joseph N World J Orthop Minireviews Artificial intelligence and machine learning in orthopaedic surgery has gained mass interest over the last decade or so. In prior studies, researchers have demonstrated that machine learning in orthopaedics can be used for different applications such as fracture detection, bone tumor diagnosis, detecting hip implant mechanical loosening, and grading osteoarthritis. As time goes on, the utility of artificial intelligence and machine learning algorithms, such as deep learning, continues to grow and expand in orthopaedic surgery. The purpose of this review is to provide an understanding of the concepts of machine learning and a background of current and future orthopaedic applications of machine learning in risk assessment, outcomes assessment, imaging, and basic science fields. In most cases, machine learning has proven to be just as effective, if not more effective, than prior methods such as logistic regression in assessment and prediction. With the help of deep learning algorithms, such as artificial neural networks and convolutional neural networks, artificial intelligence in orthopaedics has been able to improve diagnostic accuracy and speed, flag the most critical and urgent patients for immediate attention, reduce the amount of human error, reduce the strain on medical professionals, and improve care. Because machine learning has shown diagnostic and prognostic uses in orthopaedic surgery, physicians should continue to research these techniques and be trained to use these methods effectively in order to improve orthopaedic treatment. Baishideng Publishing Group Inc 2021-09-18 /pmc/articles/PMC8472446/ /pubmed/34631452 http://dx.doi.org/10.5312/wjo.v12.i9.685 Text en ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/ |
spellingShingle | Minireviews Lalehzarian, Simon P Gowd, Anirudh K Liu, Joseph N Machine learning in orthopaedic surgery |
title | Machine learning in orthopaedic surgery |
title_full | Machine learning in orthopaedic surgery |
title_fullStr | Machine learning in orthopaedic surgery |
title_full_unstemmed | Machine learning in orthopaedic surgery |
title_short | Machine learning in orthopaedic surgery |
title_sort | machine learning in orthopaedic surgery |
topic | Minireviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8472446/ https://www.ncbi.nlm.nih.gov/pubmed/34631452 http://dx.doi.org/10.5312/wjo.v12.i9.685 |
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