AIMC Topic: Neural Networks, Computer

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Classification of drug-induced hERG potassium-channel block from electrocardiographic T-wave features using artificial neural networks.

Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc
BACKGROUND: Human ether-à-go-go-related gene (hERG) potassium-channel block represents a harmful side effect of drug therapy that may cause torsade de pointes (TdP). Analysis of ventricular repolarization through electrocardiographic T-wave features ...

A difference degree test for comparing brain networks.

Human brain mapping
Recently, there has been a proliferation of methods investigating functional connectivity as a biomarker for mental disorders. Typical approaches include massive univariate testing at each edge or comparisons of network metrics to identify differing ...

A deep learning algorithm for one-step contour aware nuclei segmentation of histopathology images.

Medical & biological engineering & computing
This paper addresses the task of nuclei segmentation in high-resolution histopathology images. We propose an automatic end-to-end deep neural network algorithm for segmentation of individual nuclei. A nucleus-boundary model is introduced to predict n...

Diabetic retinopathy detection through novel tetragonal local octa patterns and extreme learning machines.

Artificial intelligence in medicine
Diabetic retinopathy (DR) is an eye disease that victimize the people suffering from diabetes from many years. The severe form of DR results in form of the blindness that can initially be controlled by the DR-screening oriented treatment. The effecti...

Consistency and differences between centrality measures across distinct classes of networks.

PloS one
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...

A generalized neural network for distributed nonsmooth optimization with inequality constraint.

Neural networks : the official journal of the International Neural Network Society
In this paper, a generalized neural network with a novel auxiliary function is proposed to solve a distributed non-differentiable optimization over a multi-agent network. The constructed auxiliary function can ensure that the state solution of propos...

Region-of-interest undersampled MRI reconstruction: A deep convolutional neural network approach.

Magnetic resonance imaging
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...

Machine learning and statistical models for predicting indoor air quality.

Indoor air
Indoor air quality (IAQ), as determined by the concentrations of indoor air pollutants, can be predicted using either physically based mechanistic models or statistical models that are driven by measured data. In comparison with mechanistic models mo...

Spread of α-synuclein pathology through the brain connectome is modulated by selective vulnerability and predicted by network analysis.

Nature neuroscience
Studies of patients afflicted by neurodegenerative diseases suggest that misfolded proteins spread through the brain along anatomically connected networks, prompting progressive decline. Recently, mouse models have recapitulated the cell-to-cell tran...

Inferring the Disease-Associated miRNAs Based on Network Representation Learning and Convolutional Neural Networks.

International journal of molecular sciences
Identification of disease-associated miRNAs (disease miRNAs) are critical for understanding etiology and pathogenesis. Most previous methods focus on integrating similarities and associating information contained in heterogeneous miRNA-disease networ...