PURPOSE: The aim of this study was to evaluate random forests (RFs) to identify ROIs on F-florbetapir and F-FDG PET associated with Montreal Cognitive Assessment (MoCA) score.
PURPOSE: To evaluate the ability of deep learning (DL) models to detect obstructive meibomian gland dysfunction (MGD) using in vivo laser confocal microscopy images.
BACKGROUND: With the improvement in diagnostic imaging, perioperative care and surgical technique, the indications and complexity of liver resections have developed. However, the surgical indications remain controversial especially for some complex o...
Robotic technology is increasingly used for sophisticated in vitro testing designed to understand the subtleties of joint biomechanics. Typically, the joint coordinate systems in these studies are established via palpation and digitization of anatomi...
INTRODUCTION: The purpose of the current study is to determine the accuracy of machine learning in predicting bleeding outcomes post percutaneous coronary intervention (PCI) in comparison with the American College of Cardiology CathPCI bleeding risk ...
BACKGROUND: Brain monitors tracking quantitative brain activities from electroencephalogram (EEG) to predict hypnotic levels have been proposed as a labor-saving alternative to behavioral assessments. Expensive clinical trials are required to validat...
BACKGROUND: Heart failure with reduced ejection fraction (HFrEF) is a condition imposing significant health care burden. Given its syndromic nature and often insidious onset, the diagnosis may not be made until clinical manifestations prompt further ...
BACKGROUND: Acute hypotensive episodes (AHE), defined as a drop in the mean arterial pressure (MAP) <65 mm Hg lasting at least 5 consecutive minutes, are among the most critical events in the intensive care unit (ICU). They are known to be associated...
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