Machine learning-based tools are capable of guiding individualized clinical management
and decision-making by providing predictions of a patient's future health state. Through their …

Background Machine learning has been increasingly used for surgical outcome prediction,
yet applications in head and neck reconstruction are not well-described. In this study, we …

Surgical complications pose significant challenges for surgeons, patients, and health care
systems as they may result in patient distress, suboptimal outcomes, and higher health care …

Abstract Background Deep learning models (DLMs) using preoperative computed
tomography (CT) imaging have shown promise in predicting outcomes following abdominal …

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

Mini-abstract The study introduces various methods of performing conventional ML and their
implementation in surgical areas, and the need to move beyond these traditional …

Introduction This systematic review aims to evaluate the use of machine learning and
artificial intelligence in hernia surgery. Methods The PRISMA guidelines were followed …

Patient-reported outcomes (PROs) enable providers to identify differences in treatment
effectiveness, postoperative recovery, quality of life, and patient satisfaction. By allowing a …

Detection of easily missed hidden patterns with fast processing power makes machine
learning (ML) indispensable to today's healthcare system. Though many ML applications …

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 …