Table 1 Basic information of included studies
From: Use of artificial neural networks in the prognosis of musculoskeletal diseases—a scoping review
Author (region) | Year of publication | Study design | Journal | Objectives | Type of disease/injury |
|---|---|---|---|---|---|
Alfieri et al. (USA) | 2015 | Cohort study | Clinical Orthopaedics and Related Research | Estimating the likelihood of wound-specific HO formation and determining (1) which model is most accurate; and (2) which technique is best suited for clinical use | Heterotopic Ossification |
Almhdie et al. (France) | 2022 | Cohort study | Arthritis Research and Therapy | To evaluate the predictive ability of a combined approach using both TBT descriptors deep learning-based Siamese CNN tools to predict KOA progression | Knee osteoarthritis |
Bevevino et al. (USA) | 2014 | Cross-sectional study | Clinical Orthopaedics and Related Research | Determining which model (artificial neural network and a logistic regression model) more accurately estimated the likelihood of amputation and which was better suited for clinical use | Combat-related Open Calcaneus Fractures |
Bowman et al. (UK) | 2018 | Cohort study | Muscle and Nerve | Develop and validate a comprehensive, multivariate prognostic model for carpal tunnel surgery in a large sample of ordinary NHS surgical procedures | Carpal tunnel syndrome |
Chen et al. (China) | 2020 | Cohort study | Medicina | To validate the accuracy of an ANN model for predicting the mortality after hip fracture surgery during the study period, and to compare performance between the ANN and Cox regression model | Hip fracture |
Eller-Vainicher et al. (Italy) | 2011 | Cohort study | PLoS One | To Comparing ANNs and LR in recognising, on the basis of osteoporotic risk-factors and other clinical information, patients with SDI ≥ 1 and SDI ≥ 5 from those with SDI = 0 | Osteoporotic fractures |
Jalali et al. (USA) | 2020 | Cohort study | Anesthesia and analgesia | Developing a machine-learning model to predict blood product transfusion requirements for individual pediatric patients undergoing craniofacial surgery | Craniosynostosis |
Kim et al. (Korea) | 2022 | Cross-sectional study | Pain Physician | Developed and investigated the accuracy of a CNN model for predicting therapeutic outcomes after TFESI for controlling chronic lumbosacral radicular pain | Chronic Lumbosacral Radicular Pain |
Kim et al. (USA) | 2018 | Cohort study | Spine Deformity | To train and validate machine learning models to identify risk factors for complications following surgery for adult ASD | Adult spinal deformity |
Lu et al. (USA) | 2021 | Cohort study | Orthopaedic journal of sports medicine | To develop and internally validate a machine-learning model to predict the outcomes after ASI | Anterior Shoulder Instability |
Miyoshi et al. (Japan) | 2016 | Cohort study | Modern rheumatology | Develop ANN model for predicting the clinical response to IFX in RA patients | Rheumatoid Arthritis |
Norgeot et al. (USA) | 2019 | Cohort study | JAMA Netw Open | To assess the ability of an artificial intelligence system to prognosticate the state of disease activity of patients with RA at their next clinical visit | Rheumatoid Arthritis |
Salgueiro et al. (Spain) | 2013 | Cohort study | Pain medicine | Evaluate the ability of ANNs to predict the response of persons with FMS to a standard, 4-week interdisciplinary pain program | Fibromyalgia syndrome |
Scheer et al. (USA) | 2017 | Cohort Study | Journal of neurosurgery. Spine | To develop a model based demographic, radiographic, and surgical factors that can predict if patients will sustain an intra/perioperative major complication | Spinal deformity |
Shin et al. (Korea) | 2022 | Cohort study | Medicina | To investigate the usefulness of DNN models based on 18F- FDG-PET and blood inflammatory markers to assess the therapeutic response in PVO | Pyogenic vertebral osteomyelitis |
Su et al. (China) | 2022 | Cohort study | Computational and Mathematical Methods in Medicine | To explore the prognostic factors of endoscopic surgery for OA and to predict the long-term efficacy of this type of surgery for OA by ANNs | Osteoarthritis |
Wang et al. (China) | 2017 | Cross-sectional study | PeerJ | Using clinical examination indicators predicts interstitial lung disease among patients with rheumatoid arthritis | Rheumatoid arthritis |
Yahara et al. (Japan) | 2022 | Cohort study | BMC musculoskeletal disorders | To develop a new diagnostic platform using DCNN to predict the risk of scoliosis progression in patients with AIS | Adolescent idiopathic scoliosis |