Editorial Commentary: Machine Learning Can Indicate Hip Arthroscopy Procedures, Predict Postoperative Improvement, and Estimate Costs.

Abstract

Complex statistical approaches are increasingly being used in the orthopaedic literature, and this is especially true in the field of sports medicine. Tools such as machine learning provide the opportunity to analyze certain research areas that would often require the complex assessment of large amounts of data. Generally, decision making is multifactorial and based upon experience, personal capabilities, available utilities, and literature. Given the difficulty associated with determining the optimal patient treatment, many studies have moved toward more complex statistical approaches to create algorithms that take large amounts of data and distill it into a formula that may guide surgeons to better patient outcomes while estimating and even optimizing costs. In the future, this clinical and economic information will play an important role in patient management.