The Role of Artificial Intelligence in Anterior Cruciate Ligament Injuries: Current Concepts and Future Perspectives.

Healthcare (Basel)

Robotic Prosthetic Surgery Unit-Sports Traumatology Unit, Fondazione Poliambulanza Istituto Ospedaliero, 25124 Brescia, Italy.

Published: January 2024

AI Article Synopsis

  • * This review explores the clinical relevance of AI tools in managing anterior cruciate ligament (ACL) reconstruction, highlighting their applications before, during, and after the surgery.
  • * There is a notable interest among orthopedic surgeons in AI applications related to ACL injuries, with an increasing number of studies suggesting a future transformation in clinical practices.

Article Abstract

The remarkable progress in data aggregation and deep learning algorithms has positioned artificial intelligence (AI) and machine learning (ML) to revolutionize the field of medicine. AI is becoming more and more prevalent in the healthcare sector, and its impact on orthopedic surgery is already evident in several fields. This review aims to examine the literature that explores the comprehensive clinical relevance of AI-based tools utilized before, during, and after anterior cruciate ligament (ACL) reconstruction. The review focuses on current clinical applications and future prospects in preoperative management, encompassing risk prediction and diagnostics; intraoperative tools, specifically navigation, identifying complex anatomic landmarks during surgery; and postoperative applications in terms of postoperative care and rehabilitation. Additionally, AI tools in educational and training settings are presented. Orthopedic surgeons are showing a growing interest in AI, as evidenced by the applications discussed in this review, particularly those related to ACL injury. The exponential increase in studies on AI tools applicable to the management of ACL tears promises a significant future impact in its clinical application, with growing attention from orthopedic surgeons.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10855330PMC
http://dx.doi.org/10.3390/healthcare12030300DOI Listing

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