This study presents a methodology for predicting the duration of surgical procedures using Machine Learning (ML). The methodology incorporates a new set of predictors emphasizing the significance of surgical team dynamics and composition, including e...
IMPORTANCE: Assessing nontechnical skills in operating rooms (ORs) is crucial for enhancing surgical performance and patient safety. However, automated and real-time evaluation of these skills remains challenging.
Journal of clinical monitoring and computing
Jun 19, 2024
Hand hygiene among anesthesia personnel is important to prevent hospital-acquired infections in operating rooms; however, an efficient monitoring system remains elusive. In this study, we leverage a deep learning approach based on operating room vide...
Robotic surgery offers potential advantages over laparoscopic procedures, but the training for configuring robotic systems in the operating room remains underexplored. This study seeks to validate immersive virtual reality (IVR) headset training for ...
PURPOSE: Surgical treatment of early-onset scoliosis (EOS) is associated with high rates of complications, often requiring unplanned return to the operating room (UPROR). The aim of this study was to create and validate a machine learning model to pr...
At the central workplace of the surgeon the digitalization of the operating room has particular consequences for the surgical work. Starting with intraoperative cross-sectional imaging and sonography, through functional imaging, minimally invasive an...
Robotic surgery represents a milestone in surgical procedures, offering advantages such as less invasive methods, elimination of tremors, scaled motion, and 3D visualization. This in-depth analysis explores the complex biochemical effects of robotic ...
This systematic review examines the recent use of artificial intelligence, particularly machine learning, in the management of operating rooms. A total of 22 selected studies from February 2019 to September 2023 are analyzed. The review emphasizes th...
Journal of cardiothoracic and vascular anesthesia
Jan 11, 2024
OBJECTIVE: To test the correlation of ejection fraction (EF) estimated by a deep-learning-based, automated algorithm (Auto EF) versus an EF estimated by Simpson's method.
INTRODUCTION: Pyeloplasties are time-sensitive, and the most common robot assisted intervention performed in pediatric urology. Early intervention is intended to avoid permanent loss of renal function with negative long-term effects if surgery is del...
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