Universität zu Köln

Feierabend, Martina ORCID: 0000-0002-2537-5832, Wolfgart, Julius Michael, Praster, Maximilian, Danalache, Marina, Migliorini, Filippo and Hofmann, Ulf Krister ORCID: 0000-0003-0589-6654 (2025). Applications of machine learning and deep learning in musculoskeletal medicine: a narrative review. European Journal of Medical Research, 30 (1). pp. 1-15. Springer Nature. ISSN 2047-783X

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Abstract

[Artikel-Nr.: 386] 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.

Item Type:	Article
Creators:	Creators Email ORCID ORCID Put Code Feierabend, Martina UNSPECIFIED https://orcid.org/0000-0002-2537-5832 UNSPECIFIED Wolfgart, Julius Michael UNSPECIFIED UNSPECIFIED UNSPECIFIED Praster, Maximilian UNSPECIFIED UNSPECIFIED UNSPECIFIED Danalache, Marina UNSPECIFIED UNSPECIFIED UNSPECIFIED Migliorini, Filippo UNSPECIFIED UNSPECIFIED UNSPECIFIED Hofmann, Ulf Krister UNSPECIFIED https://orcid.org/0000-0003-0589-6654 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-802352
Identification Number:	10.1186/s40001-025-02511-9
Journal or Publication Title:	European Journal of Medical Research
Volume:	30
Number:	1
Page Range:	pp. 1-15
Number of Pages:	15
Date:	15 May 2025
Publisher:	Springer Nature
ISSN:	2047-783X
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences
Divisions:	Key Profile Areas > Key Profile Area V: CEPLAS/Plant Science Faculty of Mathematics and Natural Sciences > Department of Biology > Botanical Institute
Subjects:	Life sciences
Uncontrolled Keywords:	Keywords Language Artificial intelligence ; Machine learning ; Supervised learning ; Unsupervised learning ; Reinforcement ; learning, Orthopaedics ; Traumatology English
['eprint_fieldname_oa_funders' not defined]:	Publikationsfonds UzK
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/80235