AIMC Topic: Neural Networks, Computer

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Spatial Clockwork Recurrent Neural Network for Muscle Perimysium Segmentation.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Accurate segmentation of perimysium plays an important role in early diagnosis of many muscle diseases because many diseases contain different perimysium inflammation. However, it remains as a challenging task due to the complex appearance of the per...

Pancreas Segmentation in MRI using Graph-Based Decision Fusion on Convolutional Neural Networks.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Automated pancreas segmentation in medical images is a prerequisite for many clinical applications, such as diabetes inspection, pancreatic cancer diagnosis, and surgical planing. In this paper, we formulate pancreas segmentation in magnetic resonanc...

Correlated EEG Signals Simulation Based on Artificial Neural Networks.

International journal of neural systems
In recent years, simulation of the human electroencephalogram (EEG) data found its important role in medical domain and neuropsychology. In this paper, a novel approach to simulation of two cross-correlated EEG signals is proposed. The proposed metho...

Developmental metaplasticity in neural circuit codes of firing and structure.

Neural networks : the official journal of the International Neural Network Society
Firing-rate dynamics have been hypothesized to mediate inter-neural information transfer in the brain. While the Hebbian paradigm, relating learning and memory to firing activity, has put synaptic efficacy variation at the center of cortical plastici...

Combining natural language processing and network analysis to examine how advocacy organizations stimulate conversation on social media.

Proceedings of the National Academy of Sciences of the United States of America
Social media sites are rapidly becoming one of the most important forums for public deliberation about advocacy issues. However, social scientists have not explained why some advocacy organizations produce social media messages that inspire far-rangi...

A comparative analysis of chaotic particle swarm optimizations for detecting single nucleotide polymorphism barcodes.

Artificial intelligence in medicine
OBJECTIVE: Evolutionary algorithms could overcome the computational limitations for the statistical evaluation of large datasets for high-order single nucleotide polymorphism (SNP) barcodes. Previous studies have proposed several chaotic particle swa...

Brain-Computer Interface for Control of Wheelchair Using Fuzzy Neural Networks.

BioMed research international
The design of brain-computer interface for the wheelchair for physically disabled people is presented. The design of the proposed system is based on receiving, processing, and classification of the electroencephalographic (EEG) signals and then perfo...

BrainNetCNN: Convolutional neural networks for brain networks; towards predicting neurodevelopment.

NeuroImage
We propose BrainNetCNN, a convolutional neural network (CNN) framework to predict clinical neurodevelopmental outcomes from brain networks. In contrast to the spatially local convolutions done in traditional image-based CNNs, our BrainNetCNN is compo...

Parkinson's disease classification using gait analysis via deterministic learning.

Neuroscience letters
Gait analysis plays an important role in maintaining the well-being of human mobility and health care, and is a valuable tool for obtaining quantitative information on motor deficits in Parkinson's disease (PD). In this paper, we propose a method to ...

Hodge Decomposition of Information Flow on Small-World Networks.

Frontiers in neural circuits
We investigate the influence of the small-world topology on the composition of information flow on networks. By appealing to the combinatorial Hodge theory, we decompose information flow generated by random threshold networks on the Watts-Strogatz mo...