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Research on artificial intelligence in shoulder and elbow surgery is increasing

BACKGROUND: Total health care spending in the United States is increasing. In order to improve our delivery of high-quality, patient-centric, and cost-effective care, artificial intelligence (AI) and its subsets are being increasingly explored and utilized in medicine. Applications of AI in orthoped...

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Autores principales: Gupta, Puneet, Marigi, Erick M., Sanchez-Sotelo, Joaquin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9937849/
https://www.ncbi.nlm.nih.gov/pubmed/36820427
http://dx.doi.org/10.1016/j.jseint.2022.10.004
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author Gupta, Puneet
Marigi, Erick M.
Sanchez-Sotelo, Joaquin
author_facet Gupta, Puneet
Marigi, Erick M.
Sanchez-Sotelo, Joaquin
author_sort Gupta, Puneet
collection PubMed
description BACKGROUND: Total health care spending in the United States is increasing. In order to improve our delivery of high-quality, patient-centric, and cost-effective care, artificial intelligence (AI) and its subsets are being increasingly explored and utilized in medicine. Applications of AI in orthopedic surgery, including shoulder and elbow surgery, are being actively studied and have stirred much discussion. However, the trends of research on AI applications in shoulder and elbow surgery have not yet been quantified. Thus, the purpose of this study is to explore the general trends of research in applying AI to shoulder and elbow surgery and to examine characteristics of these research publications. METHODS: A literature search was conducted using PubMed for all articles published between January 1, 2000 and May 12, 2022. The primary search query used was as follows: (shoulder) and (AI OR machine learning OR deep learning OR neural networks). Exclusion criteria were as follows: (1) not pertinent to orthopedic surgeons (2) not pertaining to shoulder or elbow surgery, and (3) not pertaining to AI, machine learning, and deep learning. Selected articles in high-impact and relevant orthopedic journals were further characterized and analyzed. RESULTS: The annual number of articles increased from 1 article in 2006 to 24 articles in 2021. There was a 4-fold increase in publications between 2019 and 2021, and a 6-fold increase between 2018 and 2021. The average number of publications per year increased exponentially from 2010 to 2021 (R2 = 0.608; P = .003). The three journals with the most publications were Journal of Shoulder and Elbow Surgery (12), followed by Arthroscopy (2), and Clinical Orthopaedics and Related Research (2). CONCLUSION: This study provides quantitative evidence for the first time that publications applying AI and its subsets to shoulder and elbow surgery are growing exponentially since the year 2010, with the most rapid growth beginning between the years of 2019 and 2020.
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spelling pubmed-99378492023-02-19 Research on artificial intelligence in shoulder and elbow surgery is increasing Gupta, Puneet Marigi, Erick M. Sanchez-Sotelo, Joaquin JSES Int Shoulder BACKGROUND: Total health care spending in the United States is increasing. In order to improve our delivery of high-quality, patient-centric, and cost-effective care, artificial intelligence (AI) and its subsets are being increasingly explored and utilized in medicine. Applications of AI in orthopedic surgery, including shoulder and elbow surgery, are being actively studied and have stirred much discussion. However, the trends of research on AI applications in shoulder and elbow surgery have not yet been quantified. Thus, the purpose of this study is to explore the general trends of research in applying AI to shoulder and elbow surgery and to examine characteristics of these research publications. METHODS: A literature search was conducted using PubMed for all articles published between January 1, 2000 and May 12, 2022. The primary search query used was as follows: (shoulder) and (AI OR machine learning OR deep learning OR neural networks). Exclusion criteria were as follows: (1) not pertinent to orthopedic surgeons (2) not pertaining to shoulder or elbow surgery, and (3) not pertaining to AI, machine learning, and deep learning. Selected articles in high-impact and relevant orthopedic journals were further characterized and analyzed. RESULTS: The annual number of articles increased from 1 article in 2006 to 24 articles in 2021. There was a 4-fold increase in publications between 2019 and 2021, and a 6-fold increase between 2018 and 2021. The average number of publications per year increased exponentially from 2010 to 2021 (R2 = 0.608; P = .003). The three journals with the most publications were Journal of Shoulder and Elbow Surgery (12), followed by Arthroscopy (2), and Clinical Orthopaedics and Related Research (2). CONCLUSION: This study provides quantitative evidence for the first time that publications applying AI and its subsets to shoulder and elbow surgery are growing exponentially since the year 2010, with the most rapid growth beginning between the years of 2019 and 2020. Elsevier 2022-11-02 /pmc/articles/PMC9937849/ /pubmed/36820427 http://dx.doi.org/10.1016/j.jseint.2022.10.004 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Shoulder
Gupta, Puneet
Marigi, Erick M.
Sanchez-Sotelo, Joaquin
Research on artificial intelligence in shoulder and elbow surgery is increasing
title Research on artificial intelligence in shoulder and elbow surgery is increasing
title_full Research on artificial intelligence in shoulder and elbow surgery is increasing
title_fullStr Research on artificial intelligence in shoulder and elbow surgery is increasing
title_full_unstemmed Research on artificial intelligence in shoulder and elbow surgery is increasing
title_short Research on artificial intelligence in shoulder and elbow surgery is increasing
title_sort research on artificial intelligence in shoulder and elbow surgery is increasing
topic Shoulder
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9937849/
https://www.ncbi.nlm.nih.gov/pubmed/36820427
http://dx.doi.org/10.1016/j.jseint.2022.10.004
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