BACKGROUND: We applied various machine learning algorithms to a large national dataset to model the risk of postoperative sepsis after appendectomy to evaluate utility of such methods and identify factors associated with postoperative sepsis in these...
Interactive cardiovascular and thoracic surgery
34535996
We report a bilateral thoracoscopic technique in which robot-assisted mitral valve repair was achieved concomitantly with stapler division of the large left atrial appendage. The patient was a 65-year-old male with severe mitral regurgitation, paroxy...
INTRODUCTION: Acute appendicitis is a common and time-sensitive surgical emergency, requiring rapid and accurate diagnosis and management to prevent complications. Artificial intelligence (AI) has emerged as a transformative tool in healthcare, offer...
Artificial intelligence is transforming healthcare. Artificial intelligence can improve patient care by analyzing large amounts of data to help make more informed decisions regarding treatments and enhance medical research through analyzing and inter...
BACKGROUND: Application of artificial intelligence (AI) in general surgery is evolving. Real-world implementation of an AI-based computer-vision model in laparoscopic appendectomy (LA) is presented. We aimed to evaluate (1) its accuracy in complexity...
BACKGROUND: The current scores used to help diagnose acute appendicitis have a "gray" zone in which the diagnosis is usually inconclusive. Furthermore, the universal use of CT scanning is limited because of the radiation hazards and/or limited resour...
The diagnosis of acute appendicitis and concurrent surgery referral is primarily based on clinical presentation, laboratory and radiological imaging. However, utilizing such an approach results in as much as 10-15% of negative appendectomies. Hence, ...
Medical decision making : an international journal of the Society for Medical Decision Making
39440442
BACKGROUND: Machine learning (ML) methods can identify complex patterns of treatment effect heterogeneity. However, before ML can help to personalize decision making, transparent approaches must be developed that draw on clinical judgment. We develop...
Rapid, accurate preoperative imaging diagnostics of appendicitis are critical in surgical decisions of emergency care. This study developed a fully automated diagnostic framework using a 3D convolutional neural network (CNN) to identify appendicitis ...