Background Interest in the usefulness of machine learning (ML) methods for outcomes
prediction has continued to increase in recent years. However, the advantage of advanced …

OBJECTIVES Interest in the clinical usefulness of machine learning for risk prediction has
bloomed recently. Cardiac surgery patients are at high risk of complications and therefore …

Objective: We aimed to construct and validate several machine learning (ML) algorithms to
predict long-term mortality and identify risk factors in unselected patients post-cardiac …

Importance A variety of perioperative risk factors are associated with postoperative mortality
risk. However, the relative contribution of routinely collected intraoperative clinical …

Background The benefits of cardiac surgery are sometimes difficult to predict and the
decision to operate on a given individual is complex. Machine Learning and Decision Curve …

Background This study evaluated the predictive utility of a machine learning algorithm in
estimating operative mortality risk in cardiac surgery. Methods Index adult cardiac …

OBJECTIVES Machine learning (ML) has experienced a revolutionary decade with
advances across many disciplines. We seek to understand how recent advances in ML are …

Objectives: Machine learning models used to predict postoperative mortality rarely include
intraoperative factors. Several intraoperative factors like hypotension (IOH), vasopressor …

Background Machine learning (ML) has garnered increasing attention as a means to
quantitatively analyze the growing and complex medical data to improve individualized …

Background Risk stratification plays a central role in anesthetic evaluation. The use of Big
Data and machine learning (ML) offers considerable advantages for collection and …