Artificial intelligence in planned orthopaedic care

The integration of artificial intelligence (AI) into orthopaedic care has gained considerable interest in recent years, evidenced by the growing body of literature boasting wide-ranging applications across the perioperative setting. This includes automated diagnostic imaging, clinical decision-making tools, optimisation of implant design, robotic surgery, and remote patient monitoring. Collectively, these advances propose to enhance patient care and improve system efficiency. Musculoskeletal pathologies represent the most significant contributor to global disability, with roughly 1.71 billion people afflicted, leading to an increasing volume of patients awaiting planned orthopaedic surgeries. This has exerted a considerable strain on healthcare systems globally, compounded by both the COVID-19 pandemic and the effects of an ageing population. Subsequently, patients face prolonged waiting times for surgery, with further deterioration and potentially poorer outcomes as a result. Furthermore, incorporating AI technologies into clinical practice could provide a means of addressing current and future service demands. This review aims to present a clear overview of AI applications across preoperative, intraoperative, and postoperative stages to elucidate its potential to transform planned orthopaedic care.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-11-21
DOI
https://doi.org/10.1051/sicotj/2024044/pdf
Primary Topic
Mycorrhizal Fungi and Plant Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial intelligence in planned orthopaedic care

Springer Link (Chiba Institute of Technology)
Mycorrhizal Fungi and Plant Interactions
article

Artificial intelligence in planned orthopaedic care

article en

Abstract

The integration of artificial intelligence (AI) into orthopaedic care has gained considerable interest in recent years, evidenced by the growing body of literature boasting wide-ranging applications across the perioperative setting. This includes automated diagnostic imaging, clinical decision-making tools, optimisation of implant design, robotic surgery, and remote patient monitoring. Collectively, these advances propose to enhance patient care and improve system efficiency. Musculoskeletal pathologies represent the most significant contributor to global disability, with roughly 1.71 billion people afflicted, leading to an increasing volume of patients awaiting planned orthopaedic surgeries. This has exerted a considerable strain on healthcare systems globally, compounded by both the COVID-19 pandemic and the effects of an ageing population. Subsequently, patients face prolonged waiting times for surgery, with further deterioration and potentially poorer outcomes as a result. Furthermore, incorporating AI technologies into clinical practice could provide a means of addressing current and future service demands. This review aims to present a clear overview of AI applications across preoperative, intraoperative, and postoperative stages to elucidate its potential to transform planned orthopaedic care.

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 62%
Mycorrhizal Fungi and Plant Interactions
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Artificial intelligence in planned orthopaedic care · Springer Link (Chiba Institute of Technology) (2024) | TGRS Research Map | TGRS