Healthcare systems worldwide generate vast amounts of data from many different sources.
Although of high complexity for a human being, it is essential to determine the patterns and …

Background Advances in machine learning (ML) provide great opportunities in the
prediction of hospital readmission. This review synthesizes the literature on ML methods and …

Predictive analytics play an important role in clinical research. An accurate predictive model
can help clinicians stratify risk thereby allowing the identification of a target population which …

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

Background Recent technological advances have led to the development and
implementation of machine learning (ML) in various disciplines, including neurosurgery. Our …

Simple Summary Artificial intelligence (AI) is the branch of computer science that enables
machines to learn, reason, and problem solve. In recent decades, AI has been developed …

Background We aimed to demonstrate that supervised machine learning (ML) models can
better predict postoperative complications after total shoulder arthroplasty (TSA) than …

Abstract Objectives Machine Learning and Artificial Intelligence (AI) are rapidly growing in
capability and increasingly applied to model outcomes and complications within medicine …

Background Various prognostic models are used to predict mortality and functional outcome
in patients after traumatic brain injury with a trend to incorporate machine learning protocols …

Big data has transformed into a trend phrase in healthcare and neurosurgery, becoming a
pervasive and inescapable phrase in everyday life. The upsurge in big data applications is a …