Orthopaedic Sports Medicine
Machine Learning in Orthopaedic Sports Medicine - Clinical Translation from the Registry to the Clinic
While the clinical application of machine learning to several health-care disciplines has increased considerably over recent years, it remains in its infancy in orthopaedic sports medicine. This presentation will review the basics of machine learning, give examples of how it has impacted other areas of orthopaedic surgery, and illustrate how machine learning can be applied to existing national knee ligament registers. Completed and ongoing collaborative studies between the University of Minnesota and the University of Oslo will be discussed, including a demonstration of how an in-clinic calculator was developed capable of estimating the risk of ACL reconstruction failure at a patient-specific level. Focusing on clinical translation of machine learning techniques, future opportunities within sports medicine will also be presented to stimulate idea generation and ultimately improve patient care.
R. Kyle Martin MD FRCSC is an orthopaedic sports medicine surgeon with the University of Minnesota. Originally from Canada, Dr. Martin completed his orthopaedic training at the University of Manitoba in 2017. He then travelled to Oslo, Norway where he spent one-year in a clinical fellowship with professor Lars Engebretsen at the University of Oslo and the Oslo Sports Trauma Research Center. Following the Oslo fellowship, Dr. Martin then completed a second clinical fellowship at Mayo Clinic in Rochester, MN. His current clinical practice revolves around knee, hip, and shoulder injuries and arthroscopy, while his research focus is on machine learning and its clinical applications to the field of sports medicine.