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Artificial Intelligence in the Management of Rotator Cuff Tears

Author

Listed:
  • Filippo Familiari

    (Department of Orthopaedic and Trauma Surgery, “Mater Domini” University Hospital, “Magna Græcia” University, 88100 Catanzaro, Italy)

  • Olimpio Galasso

    (Department of Orthopaedic and Trauma Surgery, “Mater Domini” University Hospital, “Magna Græcia” University, 88100 Catanzaro, Italy)

  • Federica Massazza

    (Department of Orthopaedic and Trauma Surgery, “Mater Domini” University Hospital, “Magna Græcia” University, 88100 Catanzaro, Italy)

  • Michele Mercurio

    (Department of Orthopaedic and Trauma Surgery, “Mater Domini” University Hospital, “Magna Græcia” University, 88100 Catanzaro, Italy)

  • Henry Fox

    (Department of Orthopaedic Surgery, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA)

  • Uma Srikumaran

    (Department of Orthopaedic Surgery, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA)

  • Giorgio Gasparini

    (Department of Orthopaedic and Trauma Surgery, “Mater Domini” University Hospital, “Magna Græcia” University, 88100 Catanzaro, Italy)

Abstract

Technological innovation is a key component of orthopedic surgery. Artificial intelligence (AI), which describes the ability of computers to process massive data and “learn” from it to produce outputs that mirror human cognition and problem solving, may become an important tool for orthopedic surgeons in the future. AI may be able to improve decision making, both clinically and surgically, via integrating additional data-driven problem solving into practice. The aim of this article will be to review the current applications of AI in the management of rotator cuff tears. The article will discuss various stages of the clinical course: predictive models and prognosis, diagnosis, intraoperative applications, and postoperative care and rehabilitation. Throughout the article, which is a review in terms of study design, we will introduce the concept of AI in rotator cuff tears and provide examples of how these tools can impact clinical practice and patient care. Though many advancements in AI have been made regarding evaluating rotator cuff tears—particularly in the realm of diagnostic imaging—further advancements are required before they become a regular facet of daily clinical practice.

Suggested Citation

  • Filippo Familiari & Olimpio Galasso & Federica Massazza & Michele Mercurio & Henry Fox & Uma Srikumaran & Giorgio Gasparini, 2022. "Artificial Intelligence in the Management of Rotator Cuff Tears," IJERPH, MDPI, vol. 19(24), pages 1-8, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:24:p:16779-:d:1002966
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