Background Machine learning (ML) has been introduced in various fields of healthcare. In
colorectal surgery, the role of ML has yet to be reported. In this systematic review, an …

Background Machine learning (ML) has been successful in several fields of healthcare,
however the use of ML within bariatric surgery seems to be limited. In this systematic review …

Background To assess the efficacy of artificial intelligence (AI) models in diagnosing and
prognosticating acute appendicitis (AA) in adult patients compared to traditional methods …

Aim: This study aimed to use machine learning algorithms to identify critical preoperative
variables and predict the red blood cell (RBC) transfusion during or after liver transplantation …

Background Sepsis is a life-threatening syndrome eliciting highly heterogeneous host
responses. Current prognostic evaluation methods used in clinical practice are …

Background With the integration of artificial intelligence and clinical medicine, machine
learning (ML) algorithms have been applied to develop sepsis predictive models for sepsis …

Background Nosocomial infections with heavy disease burden are becoming a major threat
to the health care system around the world. Through long-term, systematic, continuous data …

Background: Appendicitis is an inflammatory condition that requires timely and effective
intervention. Despite being one of the most common surgically treated diseases, the …

Artificial intelligence is transforming healthcare. Artificial intelligence can improve patient
care by analyzing large amounts of data to help make more informed decisions regarding …

Objectives This study aimed to use machine learning algorithms to build an efficient
forecasting model of atrial fibrillation after cardiac surgery, and to compare the predictive …