Editorial Commentary: Thoughtful Application of Artificial Intelligence Technique Improves Diagnostic Accuracy and Supportive Clinical Decision-Making.

Journal: Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
Published Date:

Abstract

Medical research within areas of deep learning, particularly in computer vision for medical imaging, has shown promise over the past decade with an increasing volume of technical papers published in orthopaedics related to imaging artificial intelligence (AI). However, as more tools and models are developed and deployed, it is easy for clinicians to get overwhelmed with the different types of models, leaving "artificial intelligence" as an empty buzzword where true value can be unclear. As with surgery, the techniques of deep learning require thoughtful application and cannot follow a one-size-fits-all approach as different problems require differential levels of technical complexity with model application. Moreover, the application of AI-based clinical tools should be both adjunctive and transparent in their stepwise integration within clinical medicine to provide additive insight. As a medical profession, we must together decide how, when, and where we want AI-based applications to offer insight.

Authors

  • Joshua J Woo
    Brown University, Providence, Rhode Island.
  • Andrew J Yang
    Brown University/The Warren Alpert School of Brown University, Providence, Rhode Island, U.S.A.
  • Ryan Y Huang
    Commons Clinic (J.J.W.); Warren Alpert Brown School of Medicine (J.J.W., A.J.Y., R.Y.H.).
  • Prem N Ramkumar
    Department of Orthopedic Surgery, Cleveland Clinic, Cleveland, OH.