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Machine learning is being used in medicine to predict outcomes for total joint replacements, but researchers warn that the accuracy of these predictions is dependent on the quality of data sources and variables included. A review of the most widely used machine learning techniques, data sources, and limitations in predictive analytics for hip and knee replacements has been published in the ANZ Journal of Surgery.