The roles of different nodes within a network are often understood through centrality analysis, which aims to quantify the capacity of a node to influence, or be influenced by, other nodes via its connection topology. Many different centrality measur...
INTRODUCTION: Ovarian tumors are the most common diagnostic challenge for gynecologists and ultrasound examination has become the main technique for assessment of ovarian pathology and for preoperative distinction between malignant and benign ovarian...
British journal of clinical pharmacology
Jul 25, 2019
Life expectancy is rising in most parts of the world as is the prevalence of chronic diseases. Suboptimal adherence to long-term medications is still rather the norm than the exception, although it is well known that suboptimal adherence compromises ...
Journal of magnetic resonance imaging : JMRI
Jul 25, 2019
Advances in both imaging and computers have led to the rise in the potential use of artificial intelligence (AI) in various tasks in breast imaging, going beyond the current use in computer-aided detection to include diagnosis, prognosis, response to...
IEEE transactions on bio-medical engineering
Jul 25, 2019
OBJECTIVE: Ultrasound elastography is gaining traction as an accessible and useful diagnostic tool for things such as, cancer detection and differentiation and thyroid disease diagnostics. Unfortunately, state-of-the-art shear wave imaging techniques...
PURPOSE: To assess the use of deep learning (DL) for computer-assisted glaucoma identification, and the impact of training using images selected by an active learning strategy, which minimizes labelling cost. Additionally, this study focuses on the e...
Progress in neuro-psychopharmacology & biological psychiatry
Jul 25, 2019
There is a growing need to address the variability in detecting cognitive deficits with standard tests in cocaine dependence (CD). The aim of the current study was to identify cognitive deficits by means of Machine Learning (ML) algorithms: Generaliz...
BACKGROUND: The aim of this study was to develop a diagnostic prediction model to improve identification of acute symptomatic portal vein thrombosis (PVT).
Compressive sensing enables fast magnetic resonance imaging (MRI) reconstruction with undersampled k-space data. However, in most existing MRI reconstruction models, the whole MR image is targeted and reconstructed without taking specific tissue regi...
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