Reinforcement learning is a powerful approach for predictive analysis to identify the weather
impacts for congenital heart disease. The key advantages of this method include the …

Objective: The aim of this study was to develop a novel machine learning model to predict
clinically relevant postoperative pancreatic fistula (CR-POPF) following …

Background Machine learning (ML) approaches have become increasingly popular in
predicting surgical outcomes. However, it is unknown whether they are superior to traditional …

Methods This prospectively registered review was conducted in accordance with the current
authoritative frameworks for scoping reviews, including studies on the use of ML to predict …

Background Precise models are necessary to estimate mortality risk following traumatic
injury to inform clinical decision making or quantify hospital performance. The Trauma and …

Artificial intelligence (AI) focuses on processing and interpreting complex information as well
as identifying relationships and patterns among complex data. Artificial intelligence-and …

Introduction Due to immunosuppression and underlying comorbidities, transplant recipients
represent a vulnerable population following emergency general surgery (EGS) operations …

Background Appendectomy remains a common pediatric surgical procedure with an
estimated 80,000 operations performed each year. While prior work has reported the …

Introduction Given the steadily aging United States population, we used a national database
to examine the association of dementia with clinical and financial outcomes following …

Postoperative respiratory failure incidents can lead to adverse outcomes, including
prolonged hospitalizations, increased admissions to intensive care units, and the risk of …