AIMC Topic: Neural Networks, Computer

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Modeling of yield and environmental impact categories in tea processing units based on artificial neural networks.

Environmental science and pollution research international
In this study, an artificial neural network (ANN) model was developed for predicting the yield and life cycle environmental impacts based on energy inputs required in processing of black tea, green tea, and oolong tea in Guilan province of Iran. A li...

Improved protein contact predictions with the MetaPSICOV2 server in CASP12.

Proteins
In this paper, we present the results for the MetaPSICOV2 contact prediction server in the CASP12 community experiment (http://predictioncenter.org). Over the 35 assessed Free Modelling target domains the MetaPSICOV2 server achieved a mean precision ...

Flexible three-dimensional artificial synapse networks with correlated learning and trainable memory capability.

Nature communications
If a three-dimensional physical electronic system emulating synapse networks could be built, that would be a significant step toward neuromorphic computing. However, the fabrication complexity of complementary metal-oxide-semiconductor architectures ...

Multi-layer network utilizing rewarded spike time dependent plasticity to learn a foraging task.

PLoS computational biology
Neural networks with a single plastic layer employing reward modulated spike time dependent plasticity (STDP) are capable of learning simple foraging tasks. Here we demonstrate advanced pattern discrimination and continuous learning in a network of s...

Real-Time Non-Invasive Detection and Classification of Diabetes Using Modified Convolution Neural Network.

IEEE journal of biomedical and health informatics
Non-invasive diabetes prediction has been gaining prominence over the last decade. Among many human serums evaluated, human breath emerges as a promising option with acetone levels in breath exhibiting a good correlation to blood glucose levels. Such...

Fuzzy-Rough Cognitive Networks.

Neural networks : the official journal of the International Neural Network Society
Rough Cognitive Networks (RCNs) are a kind of granular neural network that augments the reasoning rule present in Fuzzy Cognitive Maps with crisp information granules coming from Rough Set Theory. While RCNs have shown promise in solving different cl...

Diffusion parameter mapping with the combined intravoxel incoherent motion and kurtosis model using artificial neural networks at 3 T.

NMR in biomedicine
Artificial neural networks (ANNs) were used for voxel-wise parameter estimation with the combined intravoxel incoherent motion (IVIM) and kurtosis model facilitating robust diffusion parameter mapping in the human brain. The proposed ANN approach was...

A Deep Learning Solution for Automatic Fetal Neurosonographic Diagnostic Plane Verification Using Clinical Standard Constraints.

Ultrasound in medicine & biology
During routine ultrasound assessment of the fetal brain for biometry estimation and detection of fetal abnormalities, accurate imaging planes must be found by sonologists following a well-defined imaging protocol or clinical standard, which can be di...

A Network Pharmacology-Based Study on the Hepatoprotective Effect of Fructus Schisandrae.

Molecules (Basel, Switzerland)
(Wuweizi in Chinese), a common traditional Chinese herbal medicine, has been used for centuries to treat chronic liver disease. The therapeutic efficacy of Wuweizi has also been validated in clinical practice. In this study, molecular docking and ne...

Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals.

Computers in biology and medicine
An encephalogram (EEG) is a commonly used ancillary test to aide in the diagnosis of epilepsy. The EEG signal contains information about the electrical activity of the brain. Traditionally, neurologists employ direct visual inspection to identify epi...