American journal of infection control
Oct 29, 2024
BACKGROUND: Catheter-associated urinary tract infections (CAUTIs) increase clinical burdens. Identifying the high-risk patients is crucial. We aimed to develop and externally validate an explainable, prognostic prediction model of CAUTIs among hospit...
RATIONALE AND OBJECTIVES: Artificial intelligence (AI) algorithms in radiology capable of detecting urgent findings have gained significant traction in recent years, but the impact of these algorithms on real-world clinical practice remains unclear w...
OBJECTIVES: Introducing SPINEPS, a deep learning method for semantic and instance segmentation of 14 spinal structures (ten vertebra substructures, intervertebral discs, spinal cord, spinal canal, and sacrum) in whole-body sagittal T2-weighted turbo ...
Cardiovascular and interventional radiology
Oct 29, 2024
PURPOSE: To determine the association of machine learning-derived CT body composition and 90-day mortality after transjugular intrahepatic portosystemic shunt (TIPS) and to assess its predictive performance as a complement to Model for End-Stage Live...
Clinica chimica acta; international journal of clinical chemistry
Oct 29, 2024
BACKGROUND AND AIMS: Autism spectrum disorder (ASD) is a common neurodevelopmental disorder in children. Early intervention is effective. Investigation of novel blood biomarkers of ASD facilitates early detection and intervention.
Egg production rate and egg weight are core indicators for evaluating the production performance of broiler breeders. The accurate prediction of these indicators can significantly enhance farm economic efficiency and can provide a basis for future pr...
BACKGROUND: Lymphovascular invasion (LVI) is linked to poor prognosis in patients with muscle-invasive bladder cancer (MIBC). Accurately identifying the LVI status in MIBC patients is crucial for effective risk stratification and precision treatment....
INTRODUCTION: Multiplexed PET imaging revolutionized clinical decision-making by simultaneously capturing various radiotracer data in a single scan, enhancing diagnostic accuracy and patient comfort. Through a transformer-based deep learning, this st...
OBJECTIVES: This study aimed to develop an integrated segmentation-free deep learning (DL) framework to predict multiple aspects of radiotherapy outcome in pharyngeal cancer patients by analyzing pretreatment 18F-fluorodeoxyglucose (18F-FDG) positron...
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Oct 29, 2024
Seizure localization is important for managing drug-resistant focal epilepsy. Here, the capability of a novel deep learning-based source imaging framework (DeepSIF) for imaging seizure activities from electroencephalogram (EEG) recordings in drug-res...
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