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

被引:2
作者
Qiu, Fanji [1 ]
Li, Jinfeng [2 ]
Zhang, Rongrong [3 ]
Legerlotz, Kirsten [1 ]
机构
[1] Humboldt Univ, Inst Sport Sci, Movement Biomech, Unter Linden 6, D-10099 Berlin, Germany
[2] Iowa State Univ, Dept Kinesiol, Ames, IA 50011 USA
[3] North China Elect Power Univ, Sch Control & Comp Engn, Beijing 102206, Peoples R China
关键词
Machine learning; Musculoskeletal diseases; Prediction; GLOBAL BURDEN; MODELS; INTELLIGENCE;
D O I
10.1186/s12891-023-06195-2
中图分类号
R826.8 [整形外科学]; R782.2 [口腔颌面部整形外科学]; R726.2 [小儿整形外科学]; R62 [整形外科学(修复外科学)];
学科分类号
摘要
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.
引用
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页数:11
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