AIMC Topic: Neural Networks, Computer

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Human-inspired sound environment recognition system for assistive vehicles.

Journal of neural engineering
OBJECTIVE: The human auditory system acquires environmental information under sound stimuli faster than visual or touch systems, which in turn, allows for faster human responses to such stimuli. It also complements senses such as sight, where direct ...

Three- and four-class classification models for P-glycoprotein inhibitors using counter-propagation neural networks.

SAR and QSAR in environmental research
P-glycoprotein (P-gp) is an ATP binding cassette (ABC) transporter that helps to protect several certain human organs from xenobiotic exposure. This efflux pump is also responsible for multi-drug resistance (MDR), an issue of the chemotherapy approac...

Variations of glutamate concentration within synaptic cleft in the presence of electromagnetic fields: an artificial neural networks study.

Neurochemical research
Glutamate is an excitatory neurotransmitter that is released by the majority of central nervous system synapses and is involved in developmental processes, cognitive functions, learning and memory. Excessive elevated concentrations of Glu in synaptic...

Embedding assisted prediction architecture for event trigger identification.

Journal of bioinformatics and computational biology
Molecular events normally have significant meanings since they describe important biological interactions or alternations such as binding of a protein. As a crucial step of biological event extraction, event trigger identification has attracted much ...

A Novel Method for Automated Diagnosis of Epilepsy Using Complex-Valued Classifiers.

IEEE journal of biomedical and health informatics
The study reported herein proposes a new method for the diagnosis of epilepsy from electroencephalography (EEG) signals based on complex classifiers. To carry out this study, first the features of EEG data are extracted using a dual-tree complex wave...

Fully Connected Cascade Artificial Neural Network Architecture for Attention Deficit Hyperactivity Disorder Classification From Functional Magnetic Resonance Imaging Data.

IEEE transactions on cybernetics
Automated recognition and classification of brain diseases are of tremendous value to society. Attention deficit hyperactivity disorder (ADHD) is a diverse spectrum disorder whose diagnosis is based on behavior and hence will benefit from classificat...

On the role of astroglial syncytia in self-repairing spiking neural networks.

IEEE transactions on neural networks and learning systems
It has been shown that brain-like self-repair can arise from the interactions between neurons and astrocytes where endocannabinoids are synthesized and released from active neurons. This retrograde messenger feeds back to local synapses directly and ...

Energy-to-peak state estimation for Markov jump RNNs with time-varying delays via nonsynchronous filter with nonstationary mode transitions.

IEEE transactions on neural networks and learning systems
In this paper, the problem of energy-to-peak state estimation for a class of discrete-time Markov jump recurrent neural networks (RNNs) with randomly occurring nonlinearities (RONs) and time-varying delays is investigated. A practical phenomenon of n...

A novel neural-inspired learning algorithm with application to clinical risk prediction.

Journal of biomedical informatics
Clinical risk prediction - the estimation of the likelihood an individual is at risk of a disease - is a coveted and exigent clinical task, and a cornerstone to the recommendation of life saving management strategies. This is especially important for...

Novel method to predict body weight in children based on age and morphological facial features.

Journal of clinical pharmacology
A new and novel approach of predicting the body weight of children based on age and morphological facial features using a three-layer feed-forward artificial neural network (ANN) model is reported. The model takes in four parameters, including age-ba...