Improved Risk Prediction Following Surgery Using Machine Learning Algorithms

Abstract

The use of machine learning algorithms improves upon one commonly used risk estimator. Precisely quantifying the risk of an AE following surgery may better inform patient-centered decision-making and direct targeted quality improvement interventions while supporting activities of accountable care organizations that rely on accurate estimates of population risk.