CC2022: Sports Medicine and Artificial Intelligence: A Primer (March 2022)-CC2022: Sports Medicine and Artificial Intelligence: A Primer (March 2022)

CC2022: Sports Medicine and Artificial Intelligence: A Primer (March 2022)

Pdf Summary

Artificial intelligence (AI) is poised to transform the field of sports medicine by automating tasks and improving data-driven insights, according to a recent review article. The use of AI in orthopedic surgery and sports medicine has shown promise in predicting injury risk, interpreting advanced imaging, evaluating patient-reported outcomes, reporting value-based metrics, and enhancing the patient experience. The authors highlight the need for sports medicine specialists to have a fundamental working knowledge of AI principles in order to effectively use AI-based tools. The application of AI in medicine has been forecasted for years, but practical applications have only recently begun to materialize. In the field of sports medicine, AI technology is still in its early stages, with few studies detailing its potential applications. However, recent research efforts have demonstrated the ability of AI to predict athlete injury risk, analyze medical imaging, and identify orthopedic implants for hardware removal or revision. AI techniques such as machine learning and deep learning have been used to analyze large data sets and make predictions, and have shown superior performance compared to traditional regression analysis. While AI has the potential to improve patient care, there are also limitations and ethical considerations to consider, such as the "black box" phenomenon, data sharing, and the potential loss of human experience and clinical intuition. Despite these challenges, AI offers great promise in sports medicine and has the potential to enhance patient care and outcomes.

Keywords

Artificial intelligence

sports medicine

automating tasks

data-driven insights

orthopedic surgery

injury risk prediction

advanced imaging interpretation

patient-reported outcomes evaluation

machine learning

patient care improvement