BACKGROUND: Acute kidney injury is a common postoperative complication affecting between 10% and 30% of surgical patients. Acute kidney injury is associated with increased resource usage and chronic kidney disease development, with more severe acute ...
Clinical prediction models based on artificial intelligence algorithms can potentially improve patient care, reduce errors, and add value to the health care system. However, their adoption is hindered by legitimate economic, practical, professional, ...
BACKGROUND: Difficulty scoring systems are important for the safe, stepwise implementation of new procedures. We designed a retrospective observational study for building a difficulty score for robotic pancreatoduodenectomy.
BACKGROUND: Although the use of robotic-assisted surgery continues to expand, the cost-effectiveness of this platform remains unclear. The present study aimed to compare hospitalization costs and clinical outcomes between robotic-assisted surgery and...
BACKGROUND: Deep learning models with imbalanced data sets are a challenge in the fields of artificial intelligence and surgery. The aim of this study was to develop and compare deep learning models that predict rare but devastating postoperative com...
BACKGROUND: In the DESIRE study (Discharge aftEr Surgery usIng aRtificial intElligence), we have previously developed and validated a machine learning concept in 1,677 gastrointestinal and oncology surgery patients that can predict safe hospital disc...
BACKGROUND: Delays in admitting high-risk emergency surgery patients to the intensive care unit result in worse outcomes and increased health care costs. We aimed to use interpretable artificial intelligence technology to create a preoperative predic...