AIMC Topic: Neural Networks, Computer

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Chemical coagulation of greywater: modelling using artificial neural networks.

Water science and technology : a journal of the International Association on Water Pollution Research
In the present study, chemical coagulation with alum and polyaluminium chloride (PACl) was utilized for greywater treatment. More than 140 jar tests on greywater with varying characteristics were conducted in order to determine the optimum coagulant ...

Degradation of textile dyes Remazol Yellow Gold and reactive Turquoise: optimization, toxicity and modeling by artificial neural networks.

Water science and technology : a journal of the International Association on Water Pollution Research
In this work, the degradation of Remazol Yellow Gold RNL-150% and Reactive Turquoise Q-G125 were investigated using AOP: photolysis, UV/HO, Fenton and photo-Fenton. It was found that the photo-Fenton process employing sunlight radiation was the most ...

Modeling polypharmacy side effects with graph convolutional networks.

Bioinformatics (Oxford, England)
MOTIVATION: The use of drug combinations, termed polypharmacy, is common to treat patients with complex diseases or co-existing conditions. However, a major consequence of polypharmacy is a much higher risk of adverse side effects for the patient. Po...

Convolutional neural networks for classification of alignments of non-coding RNA sequences.

Bioinformatics (Oxford, England)
MOTIVATION: The convolutional neural network (CNN) has been applied to the classification problem of DNA sequences, with the additional purpose of motif discovery. The training of CNNs with distributed representations of four nucleotides has successf...

Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks.

JAMA ophthalmology
IMPORTANCE: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide. The decision to treat is primarily based on the presence of plus disease, defined as dilation and tortuosity of retinal vessels. However, clinical diagn...

Automatic recognition of holistic functional brain networks using iteratively optimized convolutional neural networks (IO-CNN) with weak label initialization.

Medical image analysis
fMRI data decomposition techniques have advanced significantly from shallow models such as Independent Component Analysis (ICA) and Sparse Coding and Dictionary Learning (SCDL) to deep learning models such Deep Belief Networks (DBN) and Convolutional...

γ-Aminobutyric Acid Type A Receptor Potentiation Inhibits Learning in a Computational Network Model.

Anesthesiology
BACKGROUND: Propofol produces memory impairment at concentrations well below those abolishing consciousness. Episodic memory, mediated by the hippocampus, is most sensitive. Two potentially overlapping scenarios may explain how γ-aminobutyric acid re...

Evaluation of a new neutron energy spectrum unfolding code based on an Adaptive Neuro-Fuzzy Inference System (ANFIS).

Journal of radiation research
The purpose of the present study was to reconstruct the energy spectrum of a poly-energetic neutron source using an algorithm developed based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). ANFIS is a kind of artificial neural network based on t...

MIIC online: a web server to reconstruct causal or non-causal networks from non-perturbative data.

Bioinformatics (Oxford, England)
SUMMARY: We present a web server running the MIIC algorithm, a network learning method combining constraint-based and information-theoretic frameworks to reconstruct causal, non-causal or mixed networks from non-perturbative data, without the need fo...