Objectives In this systematic review we aimed at assessing how artificial intelligence (AI),
including machine learning (ML) techniques have been deployed to predict, diagnose, and …

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

Background and Objective The aim of this narrative review is to analyze whether or not
artificial intelligence (AI) and its subsets are implemented in current clinical anesthetic …

Objective Surgical outcome prediction is challenging but necessary for postoperative
management. Current machine learning models utilize pre-and post-op data, excluding …

Arterial hypotension is associated with incidence of postoperative complications, such as
myocardial infarction or acute kidney injury. Little research has been conducted for the real …

Anesthesia is the process of inducing and experiencing various conditions, such as
painlessness, immobility, and amnesia, to facilitate surgeries and other medical procedures …

Background We lack evidence on the cumulative effectiveness of machine learning (ML)-
driven interventions in perioperative settings. Therefore, we conducted a systematic review …

Background and objectives: cardiovascular complications (CVC) are the leading cause of
death in patients with chronic kidney disease (CKD). Standard cardiovascular disease risk …

Background: In predicting post-operative outcomes for patients with end-stage renal
disease, our study faced challenges related to class imbalance and a high-dimensional …