AIMC Topic: Neural Networks, Computer

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Detecting central fixation by means of artificial neural networks in a pediatric vision screener using retinal birefringence scanning.

Biomedical engineering online
BACKGROUND: Reliable detection of central fixation and eye alignment is essential in the diagnosis of amblyopia ("lazy eye"), which can lead to blindness. Our lab has developed and reported earlier a pediatric vision screener that performs scanning o...

Early Detection of Peak Demand Days of Chronic Respiratory Diseases Emergency Department Visits Using Artificial Neural Networks.

IEEE journal of biomedical and health informatics
Chronic respiratory diseases, mainly asthma and chronic obstructive pulmonary disease (COPD), affect the lives of people by limiting their activities in various aspects. Overcrowding of hospital emergency departments (EDs) due to respiratory diseases...

A universal multilingual weightless neural network tagger via quantitative linguistics.

Neural networks : the official journal of the International Neural Network Society
In the last decade, given the availability of corpora in several distinct languages, research on multilingual part-of-speech tagging started to grow. Amongst the novelties there is mWANN-Tagger (multilingual weightless artificial neural network tagge...

Robust stability analysis of quaternion-valued neural networks with time delays and parameter uncertainties.

Neural networks : the official journal of the International Neural Network Society
This paper addresses the problem of robust stability for quaternion-valued neural networks (QVNNs) with leakage delay, discrete delay and parameter uncertainties. Based on Homeomorphic mapping theorem and Lyapunov theorem, via modulus inequality tech...

In Silico Prediction of Chemicals Binding to Aromatase with Machine Learning Methods.

Chemical research in toxicology
Environmental chemicals may affect endocrine systems through multiple mechanisms, one of which is via effects on aromatase (also known as CYP19A1), an enzyme critical for maintaining the normal balance of estrogens and androgens in the body. Therefor...

Neural networks subtract and conquer.

eLife
Two theoretical studies reveal how networks of neurons may behave during reward-based learning.

A novel model-based on FCM-LM algorithm for prediction of protein folding rate.

Journal of bioinformatics and computational biology
The prediction of protein folding rates is of paramount importance in describing the protein folding mechanism, which has broad applications in fields such as enzyme engineering and protein engineering. Therefore, predicting protein folding rates usi...

Hopfield networks as a model of prototype-based category learning: A method to distinguish trained, spurious, and prototypical attractors.

Neural networks : the official journal of the International Neural Network Society
We present an investigation of the potential use of Hopfield networks to learn neurally plausible, distributed representations of category prototypes. Hopfield networks are dynamical models of autoassociative memory which learn to recreate a set of i...

Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural Networks.

Radiology
Purpose To evaluate the efficacy of deep convolutional neural networks (DCNNs) for detecting tuberculosis (TB) on chest radiographs. Materials and Methods Four deidentified HIPAA-compliant datasets were used in this study that were exempted from revi...

Spatiotemporal signal classification via principal components of reservoir states.

Neural networks : the official journal of the International Neural Network Society
Reservoir computing is a recently introduced machine learning paradigm that has been shown to be well-suited for the processing of spatiotemporal data. Rather than training the network node connections and weights via backpropagation in traditional r...