While people 65 years of age and older represent 16% of the population in the United
States, they account for> 40% of surgical procedures performed each year. Maintaining …

Background The utilization of artificial intelligence and machine learning as diagnostic and
predictive tools in perioperative medicine holds great promise. Indeed, many studies have …

Background Accurate, pragmatic risk stratification for postoperative delirium (POD) is
necessary to target preventative resources toward high-risk patients. Machine learning (ML) …

To evaluate the performance of machine learning (ML) models and to compare it with
logistic regression (LR) technique in predicting cognitive impairment related to post …

Aims To compare the performance of logistic regression and machine learning methods in
predicting postoperative delirium (POD) in elderly patients. Method This was a retrospective …

Study objective To develop and validate a simple delirium-predicting scoring system in
patients undergoing major abdominal surgery by incorporating preoperative risk factors and …

Introduction: The number of elective surgeries for patients who are over 70 years of age is
continuously growing. At the same time, postoperative delirium (POD) is common in older …

Introduction Delirium is a cerebral dysfunction seen commonly in the acute care setting. It is
associated with increased mortality and morbidity and is frequently missed in the emergency …

Background Postoperative delirium is a common complication that is distressing. This study
aimed to demonstrate a prediction model for delirium. Methods Among 203,374 undergoing …

Objective Postoperative delirium (POD) is a common postoperative complication in elderly
patients, especially those undergoing cardiac surgery, which seriously affects the short-and …