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Artificial Intelligence in the Management of Rotator Cuff Tears
Technological innovation is a key component of orthopedic surgery. Artificial intelligence (AI), which describes the ability of computers to process massive data and “learn” from it to produce outputs that mirror human cognition and problem solving, may become an important tool for orthopedic surgeo...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9779744/ https://www.ncbi.nlm.nih.gov/pubmed/36554660 http://dx.doi.org/10.3390/ijerph192416779 |
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author | Familiari, Filippo Galasso, Olimpio Massazza, Federica Mercurio, Michele Fox, Henry Srikumaran, Uma Gasparini, Giorgio |
author_facet | Familiari, Filippo Galasso, Olimpio Massazza, Federica Mercurio, Michele Fox, Henry Srikumaran, Uma Gasparini, Giorgio |
author_sort | Familiari, Filippo |
collection | PubMed |
description | Technological innovation is a key component of orthopedic surgery. Artificial intelligence (AI), which describes the ability of computers to process massive data and “learn” from it to produce outputs that mirror human cognition and problem solving, may become an important tool for orthopedic surgeons in the future. AI may be able to improve decision making, both clinically and surgically, via integrating additional data-driven problem solving into practice. The aim of this article will be to review the current applications of AI in the management of rotator cuff tears. The article will discuss various stages of the clinical course: predictive models and prognosis, diagnosis, intraoperative applications, and postoperative care and rehabilitation. Throughout the article, which is a review in terms of study design, we will introduce the concept of AI in rotator cuff tears and provide examples of how these tools can impact clinical practice and patient care. Though many advancements in AI have been made regarding evaluating rotator cuff tears—particularly in the realm of diagnostic imaging—further advancements are required before they become a regular facet of daily clinical practice. |
format | Online Article Text |
id | pubmed-9779744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97797442022-12-23 Artificial Intelligence in the Management of Rotator Cuff Tears Familiari, Filippo Galasso, Olimpio Massazza, Federica Mercurio, Michele Fox, Henry Srikumaran, Uma Gasparini, Giorgio Int J Environ Res Public Health Review Technological innovation is a key component of orthopedic surgery. Artificial intelligence (AI), which describes the ability of computers to process massive data and “learn” from it to produce outputs that mirror human cognition and problem solving, may become an important tool for orthopedic surgeons in the future. AI may be able to improve decision making, both clinically and surgically, via integrating additional data-driven problem solving into practice. The aim of this article will be to review the current applications of AI in the management of rotator cuff tears. The article will discuss various stages of the clinical course: predictive models and prognosis, diagnosis, intraoperative applications, and postoperative care and rehabilitation. Throughout the article, which is a review in terms of study design, we will introduce the concept of AI in rotator cuff tears and provide examples of how these tools can impact clinical practice and patient care. Though many advancements in AI have been made regarding evaluating rotator cuff tears—particularly in the realm of diagnostic imaging—further advancements are required before they become a regular facet of daily clinical practice. MDPI 2022-12-14 /pmc/articles/PMC9779744/ /pubmed/36554660 http://dx.doi.org/10.3390/ijerph192416779 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Familiari, Filippo Galasso, Olimpio Massazza, Federica Mercurio, Michele Fox, Henry Srikumaran, Uma Gasparini, Giorgio Artificial Intelligence in the Management of Rotator Cuff Tears |
title | Artificial Intelligence in the Management of Rotator Cuff Tears |
title_full | Artificial Intelligence in the Management of Rotator Cuff Tears |
title_fullStr | Artificial Intelligence in the Management of Rotator Cuff Tears |
title_full_unstemmed | Artificial Intelligence in the Management of Rotator Cuff Tears |
title_short | Artificial Intelligence in the Management of Rotator Cuff Tears |
title_sort | artificial intelligence in the management of rotator cuff tears |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9779744/ https://www.ncbi.nlm.nih.gov/pubmed/36554660 http://dx.doi.org/10.3390/ijerph192416779 |
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