Applications of machine learning and deep learning in musculoskeletal medicine: a narrative review
Abstract Artificial intelligence (AI), with its technologies such as machine perception, robotics, natural language processing, expert systems, and machine learning (ML) with its subset deep learning, have transformed patient care and administration in all fields of modern medicine. For many clinici...
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| Format: | Article |
| Language: | English |
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BMC
2025-05-01
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| Series: | European Journal of Medical Research |
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| Online Access: | https://doi.org/10.1186/s40001-025-02511-9 |
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| author | Martina Feierabend Julius Michael Wolfgart Maximilian Praster Marina Danalache Filippo Migliorini Ulf Krister Hofmann |
| author_facet | Martina Feierabend Julius Michael Wolfgart Maximilian Praster Marina Danalache Filippo Migliorini Ulf Krister Hofmann |
| author_sort | Martina Feierabend |
| collection | DOAJ |
| description | Abstract Artificial intelligence (AI), with its technologies such as machine perception, robotics, natural language processing, expert systems, and machine learning (ML) with its subset deep learning, have transformed patient care and administration in all fields of modern medicine. For many clinicians, however, the nature, scope, and resulting possibilities of ML and deep learning might not yet be fully clear. This narrative review provides an overview of the application of ML and deep learning in musculoskeletal medicine. It first introduces the concept of AI and machine learning and its associated fields. Different machine concepts such as supervised, unsupervised and reinforcement learning will then be presented with current applications and clinical perspective. Finally deep learning applications will be discussed. With significant improvements over the last decade, ML and its subset deep learning today offer potent tools for numerous applications to implement in clinical practice. While initial setup costs are high, these investments can reduce workload and cost globally. At the same time, many challenges remain, such as standardisation in data labelling and often insufficient validity of the obtained results. In addition, legal aspects still will have to be clarified. Until good analyses and predictions are obtained by an ML tool, patience in training and suitable data sets are required. Awareness of the strengths of ML and the limitations that lie within it will help put this technique to good use. |
| format | Article |
| id | doaj-art-7698174d9c2248e9abcab10aeaeaba56 |
| institution | OA Journals |
| issn | 2047-783X |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMC |
| record_format | Article |
| series | European Journal of Medical Research |
| spelling | doaj-art-7698174d9c2248e9abcab10aeaeaba562025-08-20T01:51:28ZengBMCEuropean Journal of Medical Research2047-783X2025-05-0130111510.1186/s40001-025-02511-9Applications of machine learning and deep learning in musculoskeletal medicine: a narrative reviewMartina Feierabend0Julius Michael Wolfgart1Maximilian Praster2Marina Danalache3Filippo Migliorini4Ulf Krister Hofmann5Metabolic Reconstruction and Flux Modelling, University of CologneDepartment of Orthopaedic, Trauma, and Reconstructive Surgery, RWTH University HospitalDepartment of Orthopaedic, Trauma, and Reconstructive Surgery, Division of Arthroplasty and Tumour Surgery, RWTH University HospitalDepartment of Orthopaedic Surgery, University Hospital TübingenDepartment of Orthopaedic and Trauma Surgery, Academic Hospital of Bolzano (SABES-ASDAA), Teaching Hospital of the Paracelsus Medical UniversityDepartment of Orthopaedic, Trauma, and Reconstructive Surgery, Division of Arthroplasty and Tumour Surgery, RWTH University HospitalAbstract Artificial intelligence (AI), with its technologies such as machine perception, robotics, natural language processing, expert systems, and machine learning (ML) with its subset deep learning, have transformed patient care and administration in all fields of modern medicine. For many clinicians, however, the nature, scope, and resulting possibilities of ML and deep learning might not yet be fully clear. This narrative review provides an overview of the application of ML and deep learning in musculoskeletal medicine. It first introduces the concept of AI and machine learning and its associated fields. Different machine concepts such as supervised, unsupervised and reinforcement learning will then be presented with current applications and clinical perspective. Finally deep learning applications will be discussed. With significant improvements over the last decade, ML and its subset deep learning today offer potent tools for numerous applications to implement in clinical practice. While initial setup costs are high, these investments can reduce workload and cost globally. At the same time, many challenges remain, such as standardisation in data labelling and often insufficient validity of the obtained results. In addition, legal aspects still will have to be clarified. Until good analyses and predictions are obtained by an ML tool, patience in training and suitable data sets are required. Awareness of the strengths of ML and the limitations that lie within it will help put this technique to good use.https://doi.org/10.1186/s40001-025-02511-9Artificial intelligenceMachine learningSupervised learningUnsupervised learningReinforcement learningOrthopaedics |
| spellingShingle | Martina Feierabend Julius Michael Wolfgart Maximilian Praster Marina Danalache Filippo Migliorini Ulf Krister Hofmann Applications of machine learning and deep learning in musculoskeletal medicine: a narrative review European Journal of Medical Research Artificial intelligence Machine learning Supervised learning Unsupervised learning Reinforcement learning Orthopaedics |
| title | Applications of machine learning and deep learning in musculoskeletal medicine: a narrative review |
| title_full | Applications of machine learning and deep learning in musculoskeletal medicine: a narrative review |
| title_fullStr | Applications of machine learning and deep learning in musculoskeletal medicine: a narrative review |
| title_full_unstemmed | Applications of machine learning and deep learning in musculoskeletal medicine: a narrative review |
| title_short | Applications of machine learning and deep learning in musculoskeletal medicine: a narrative review |
| title_sort | applications of machine learning and deep learning in musculoskeletal medicine a narrative review |
| topic | Artificial intelligence Machine learning Supervised learning Unsupervised learning Reinforcement learning Orthopaedics |
| url | https://doi.org/10.1186/s40001-025-02511-9 |
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