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Use of artificial neural networks in the prognosis of musculoskeletal diseases—a scoping review

To determine the current evidence on artificial neural network (ANN) in prognostic studies of musculoskeletal diseases (MSD) and to assess the accuracy of ANN in predicting the prognosis of patients with MSD. The scoping review was reported under the Preferred Items for Systematic Reviews and the Me...

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Autores principales: Qiu, Fanji, Li, Jinfeng, Zhang, Rongrong, Legerlotz, Kirsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9890715/
https://www.ncbi.nlm.nih.gov/pubmed/36726111
http://dx.doi.org/10.1186/s12891-023-06195-2
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author Qiu, Fanji
Li, Jinfeng
Zhang, Rongrong
Legerlotz, Kirsten
author_facet Qiu, Fanji
Li, Jinfeng
Zhang, Rongrong
Legerlotz, Kirsten
author_sort Qiu, Fanji
collection PubMed
description To determine the current evidence on artificial neural network (ANN) in prognostic studies of musculoskeletal diseases (MSD) and to assess the accuracy of ANN in predicting the prognosis of patients with MSD. The scoping review was reported under the Preferred Items for Systematic Reviews and the Meta-Analyses extension for Scope Reviews (PRISMA-ScR). Cochrane Library, Embase, Pubmed, and Web of science core collection were searched from inception to January 2023. Studies were eligible if they used ANN to make predictions about MSD prognosis. Variables, model prediction accuracy, and disease type used in the ANN model were extracted and charted, then presented as a table along with narrative synthesis. Eighteen Studies were included in this scoping review, with 16 different types of musculoskeletal diseases. The accuracy of the ANN model predictions ranged from 0.542 to 0.947. ANN models were more accurate compared to traditional logistic regression models. This scoping review suggests that ANN can predict the prognosis of musculoskeletal diseases, which has the potential to be applied to different types of MSD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12891-023-06195-2.
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spelling pubmed-98907152023-02-02 Use of artificial neural networks in the prognosis of musculoskeletal diseases—a scoping review Qiu, Fanji Li, Jinfeng Zhang, Rongrong Legerlotz, Kirsten BMC Musculoskelet Disord Research To determine the current evidence on artificial neural network (ANN) in prognostic studies of musculoskeletal diseases (MSD) and to assess the accuracy of ANN in predicting the prognosis of patients with MSD. The scoping review was reported under the Preferred Items for Systematic Reviews and the Meta-Analyses extension for Scope Reviews (PRISMA-ScR). Cochrane Library, Embase, Pubmed, and Web of science core collection were searched from inception to January 2023. Studies were eligible if they used ANN to make predictions about MSD prognosis. Variables, model prediction accuracy, and disease type used in the ANN model were extracted and charted, then presented as a table along with narrative synthesis. Eighteen Studies were included in this scoping review, with 16 different types of musculoskeletal diseases. The accuracy of the ANN model predictions ranged from 0.542 to 0.947. ANN models were more accurate compared to traditional logistic regression models. This scoping review suggests that ANN can predict the prognosis of musculoskeletal diseases, which has the potential to be applied to different types of MSD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12891-023-06195-2. BioMed Central 2023-02-01 /pmc/articles/PMC9890715/ /pubmed/36726111 http://dx.doi.org/10.1186/s12891-023-06195-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Qiu, Fanji
Li, Jinfeng
Zhang, Rongrong
Legerlotz, Kirsten
Use of artificial neural networks in the prognosis of musculoskeletal diseases—a scoping review
title Use of artificial neural networks in the prognosis of musculoskeletal diseases—a scoping review
title_full Use of artificial neural networks in the prognosis of musculoskeletal diseases—a scoping review
title_fullStr Use of artificial neural networks in the prognosis of musculoskeletal diseases—a scoping review
title_full_unstemmed Use of artificial neural networks in the prognosis of musculoskeletal diseases—a scoping review
title_short Use of artificial neural networks in the prognosis of musculoskeletal diseases—a scoping review
title_sort use of artificial neural networks in the prognosis of musculoskeletal diseases—a scoping review
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9890715/
https://www.ncbi.nlm.nih.gov/pubmed/36726111
http://dx.doi.org/10.1186/s12891-023-06195-2
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