IMR Press / FBL / Volume 26 / Issue 11 / DOI: 10.52586/5027
Open Access Review
Artificial intelligence in musculoskeletal conditions
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1 Department of Physical Medicine and Rehabilitation, Cruz Roja San José y Santa Adela University Hospital, 28003 Madrid, Spain
2 Department of Physical Medicine and Rehabilitation, La Paz University Hospital, 28046 Madrid, Spain
3 Department of Orthopedic Surgery, La Paz University Hospital, 28046 Madrid, Spain
4 Osteoarticular Surgery Research, Hospital La Paz Institute for Health Research – IdiPAZ (La Paz University Hospital – Autonomous University of Madrid), 28046 Madrid, Spain
Front. Biosci. (Landmark Ed) 2021, 26(11), 1340–1348; https://doi.org/10.52586/5027
Submitted: 5 August 2021 | Revised: 23 September 2021 | Accepted: 22 October 2021 | Published: 30 November 2021
Copyright: © 2021 The Author(s). Published by BRI.
This is an open access article under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/).
Abstract

Artificial intelligence (AI) is an iterative process by which information is captured, transformed into knowledge and processed to produce adaptive changes in the environment. AI is a broad concept, involving virtual (computing) and physical (robotics) elements. In this narrative literature review, we focus on the aspects of AI that present major opportunities for developing health care. Within a few years, AI will be part of our daily clinical practice. Although significant advances are being made, the application of AI in musculoskeletal medicine is still in its early stages compared with its implementation in other areas of medicine. AI is increasingly being employed in fields such as musculoskeletal radiology, skeletal trauma, orthopedic surgery, physical and rehabilitation medicine and sports medicine, as well as for “big data” and AI in gastrointestinal (GI) endoscopy related injuries. Among the limitations of IA are that it analyzes information based on the data it is supplied, which must therefore be well-labeled and that some algorithms such as DL uses more time, data, and computational power than other techniques. Moreover, AI currently does not solve the problem of causality that exists in medicine with observational data; information that physicians interpret within a broad clinical context. AI should therefore be integrated in a prudent and reasonable manner into the workflows of health professionals.

Keywords
Artificial intelligence
Musculoskeletal radiology
Skeletal trauma
Physical and rehabilitation medicine
Orthopedic surgery
Sports medicine
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