AIMC Topic: Neural Networks, Computer

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[Intelligent systems tools in the diagnosis of acute coronary syndromes: A systemic review].

Archivos de cardiologia de Mexico
BACKGROUND: Acute myocardial infarction is the leading cause of non-communicable deaths worldwide. Its diagnosis is a highly complex task, for which modelling through automated methods has been attempted. A systematic review of the literature was per...

Automated Identification of Diabetic Retinopathy Using Deep Learning.

Ophthalmology
PURPOSE: Diabetic retinopathy (DR) is one of the leading causes of preventable blindness globally. Performing retinal screening examinations on all diabetic patients is an unmet need, and there are many undiagnosed and untreated cases of DR. The obje...

A multi-resolution approach for spinal metastasis detection using deep Siamese neural networks.

Computers in biology and medicine
Spinal metastasis, a metastatic cancer of the spine, is the most common malignant disease in the spine. In this study, we investigate the feasibility of automated spinal metastasis detection in magnetic resonance imaging (MRI) by using deep learning ...

Mapping brain structure and function: cellular resolution, global perspective.

Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology
A comprehensive understanding of the brain requires analysis, although from a global perspective, with cellular, and even subcellular, resolution. An important step towards this goal involves the establishment of three-dimensional high-resolution bra...

Autoassociative Memory and Pattern Recognition in Micromechanical Oscillator Network.

Scientific reports
Towards practical realization of brain-inspired computing in a scalable physical system, we investigate a network of coupled micromechanical oscillators. We numerically simulate this array of all-to-all coupled nonlinear oscillators in the presence o...

A top-down manner-based DCNN architecture for semantic image segmentation.

PloS one
Given their powerful feature representation for recognition, deep convolutional neural networks (DCNNs) have been driving rapid advances in high-level computer vision tasks. However, their performance in semantic image segmentation is still not satis...

Gland Instance Segmentation Using Deep Multichannel Neural Networks.

IEEE transactions on bio-medical engineering
OBJECTIVE: A new image instance segmentation method is proposed to segment individual glands (instances) in colon histology images. This process is challenging since the glands not only need to be segmented from a complex background, they must also b...

Robust fixed-time synchronization for uncertain complex-valued neural networks with discontinuous activation functions.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the fixed-time synchronization for a class of complex-valued neural networks in the presence of discontinuous activation functions and parameter uncertainties. Fixed-time synchronization not only claims that the considere...

The attractor recurrent neural network based on fuzzy functions: An effective model for the classification of lung abnormalities.

Computers in biology and medicine
The respiratory system dynamic is of high significance when it comes to the detection of lung abnormalities, which highlights the importance of presenting a reliable model for it. In this paper, we introduce a novel dynamic modelling method for the c...

Persistent irregular activity is a result of rebound and coincident detection mechanisms: A computational study.

Neural networks : the official journal of the International Neural Network Society
Persistent irregular activity is defined as elevated irregular neural discharges in the brain in such a way that while the average network activity displays high frequency oscillations, the participating neurons display irregular and low frequency os...