The Purpose of the study was to develop a deep residual learning algorithm to screen for glaucoma from fundus photography and measure its diagnostic performance compared to Residents in Ophthalmology. A training dataset consisted of 1,364 color fundu...
OBJECTIVE: High breast density is a risk factor for breast cancer. The aim of this study was to develop a deep convolutional neural network (dCNN) for the automatic classification of breast density based on the mammographic appearance of the tissue a...
Artificial intelligence (AI) has emerged as a major frontier in computer science research. Although AI has broad application across many medical fields, it will have particular utility in ophthalmology and will dramatically change the diagnostic and ...
IEEE journal of biomedical and health informatics
Sep 28, 2018
Automatic retinal vessel segmentation is a fundamental step in the diagnosis of eye-related diseases, in which both thick vessels and thin vessels are important features for symptom detection. All existing deep learning models attempt to segment both...
IEEE transactions on bio-medical engineering
Sep 28, 2018
It is largely unknown whether there is functional role difference between cortical gyral and sulcal regions. Recent advancements in neuroimaging studies demonstrate clear difference of structural connection profiles in gyral and sulcal areas, suggest...
BACKGROUND: The large amount of clinical signals in intensive care units can easily overwhelm health-care personnel and can lead to treatment delays, suboptimal care, or clinical errors. The aim of this study was to apply deep machine learning method...
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Sep 27, 2018
Combined analysis of SPECT myocardial perfusion imaging (MPI) performed with a solid-state camera on patients in 2 positions (semiupright, supine) is routinely used to mitigate attenuation artifacts. We evaluated the prediction of obstructive disease...
Neural networks : the official journal of the International Neural Network Society
Sep 27, 2018
Learning in physical neural systems must rely on learning rules that are local in both space and time. Optimal learning in deep neural architectures requires that non-local information be available to the deep synapses. Thus, in general, optimal lear...
While convolutional neural networks (CNNs) have successfully been applied for skin lesion classification, previous studies have generally considered only a single clinical/macroscopic image and output a binary decision. In this work, we have presente...
Protein nitration and nitrosylation are essential post-translational modifications (PTMs) involved in many fundamental cellular processes. Recent studies have revealed that excessive levels of nitration and nitrosylation in some critical proteins are...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.