The rapid spread of the severe acute respiratory syndrome coronavirus 2 led to a global overextension of healthcare. Both Chest X-rays (CXR) and blood test have been demonstrated to have predictive value on Coronavirus Disease 2019 (COVID-19) diagnos...
Falls are a significant ongoing public health concern for older adults. At present, few studies have concurrently explored the influence of multiple measures when seeking to determine which variables are most predictive of fall risks. As such, this c...
Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists
Oct 30, 2023
PURPOSE: Artificial intelligence (AI) using an automated, deep learning-based method, Augmented Radiology for Vascular Aneurysm (ARVA), has been verified as a viable aide in aneurysm morphology assessment. The aim of this study was to evaluate the ac...
The Journal of thoracic and cardiovascular surgery
Oct 30, 2023
OBJECTIVES: This study aimed to evaluate the safety and feasibility of early chest tube removal after anatomic pulmonary resection, regardless of the drainage volume.
Computer methods and programs in biomedicine
Oct 30, 2023
BACKGROUND: White matter hyperintensities (WMHs) are widely-seen in the aging population, which are associated with cerebrovascular risk factors and age-related cognitive decline. At present, structural atrophy and functional alterations coexisted wi...
A super-resolution deep learning reconstruction (SR-DLR) algorithm trained using data acquired on the ultrahigh spatial resolution computed tomography (UHRCT) has the potential to provide better image quality of coronary arteries on the whole-heart, ...
INTRODUCTION: Assistive and service robots have been increasingly designed and deployed in long-term care (LTC) but little evidence guides their use. This scoping review synthesises existing studies on facilitators and barriers to using artificial in...
Journal of magnetic resonance imaging : JMRI
Oct 28, 2023
BACKGROUND: Accurate preoperative histological stratification (HS) of intracranial solitary fibrous tumors (ISFTs) can help predict patient outcomes and develop personalized treatment plans. However, the role of a comprehensive model based on clinica...
OBJECTIVES: To develop a deep learning (DL) for detection of brain metastasis (BM) that incorporates both gradient- and turbo spin-echo contrast-enhanced MRI (dual-enhanced DL) and evaluate it in a clinical cohort in comparison with human readers and...
In this study, Neural Networks (NN) modelling has emerged as a promising tool for predicting outcomes in patients with Brain Stroke (BS) by identifying key risk factors. In this longitudinal study, we enrolled 332 patients form Imam hospital in Ardab...
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