OBJECTIVE: Most deep neural networks (DNNs) used as brain computer interfaces (BCI) classifiers are rarely viable for more than one person and are relatively shallow compared to the state-of-the-art in the wider machine learning literature. The goal ...
Translational vision science & technology
Oct 13, 2020
PURPOSE: To use a deep learning model to develop a fully automated method (fully semantic network and graph search [FS-GS]) of retinal segmentation for optical coherence tomography (OCT) images from patients with Stargardt disease.
Cerebral Microbleeds (CMBs) are small chronic brain hemorrhages, which have been considered as diagnostic indicators for different cerebrovascular diseases including stroke, dysfunction, dementia, and cognitive impairment. However, automated detectio...
The objective of the study was to evaluate the risk of bleeding complications in patients undergoing robot-assisted radical prostatectomy (RARP) while taking antiplatelet (AP) and/or anticoagulant (AC) agents. We analyzed the data of 334 patients und...
Internet gaming disorder (IGD), a worldwide mental health issue, has been widely studied using neuroimaging techniques during the last decade. Although dysfunctions in resting-state functional connectivity have been reported in IGD, mapping relations...
Retinal blood vessels provide information on the risk of cardiovascular disease (CVD). Here, we report the development and validation of deep-learning models for the automated measurement of retinal-vessel calibre in retinal photographs, using divers...
Artificial intelligence (AI) has influenced every field of cardiovascular imaging in all phases from acquisition to reporting. Compared with computed tomography and magnetic resonance imaging, there is an issue of high observer variation in the inter...
Neural networks : the official journal of the International Neural Network Society
Oct 12, 2020
In computational neuroscience, as well as in machine learning, neuromorphic devices promise an accelerated and scalable alternative to neural network simulations. Their neural connectivity and synaptic capacity depend on their specific design choices...
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