AIMC Topic: Neural Networks, Computer

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A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction.

BMC bioinformatics
BACKGROUND: Direct prediction of the three-dimensional (3D) structures of proteins from one-dimensional (1D) sequences is a challenging problem. Significant structural characteristics such as solvent accessibility and contact number are essential for...

Deep learning architectures for multi-label classification of intelligent health risk prediction.

BMC bioinformatics
BACKGROUND: Multi-label classification of data remains to be a challenging problem. Because of the complexity of the data, it is sometimes difficult to infer information about classes that are not mutually exclusive. For medical data, patients could ...

Development of models for predicting Torsade de Pointes cardiac arrhythmias using perceptron neural networks.

BMC bioinformatics
BACKGROUND: Blockage of some ion channels and in particular, the hERG (human Ether-a'-go-go-Related Gene) cardiac potassium channel delays cardiac repolarization and can induce arrhythmia. In some cases it leads to a potentially life-threatening arrh...

Pseudoneglect in Visual Search: Behavioral Evidence and Connectional Constraints in Simulated Neural Circuitry.

eNeuro
Most people tend to bisect horizontal lines slightly to the left of their true center (pseudoneglect) and start visual search from left-sided items. This physiological leftward spatial bias may depend on hemispheric asymmetries in the organization of...

Deep vector-based convolutional neural network approach for automatic recognition of colonies of induced pluripotent stem cells.

PloS one
Pluripotent stem cells can potentially be used in clinical applications as a model for studying disease progress. This tracking of disease-causing events in cells requires constant assessment of the quality of stem cells. Existing approaches are inad...

Optimization of Solvent Terminated Dispersive Liquid-Liquid Microextraction of Copper Ions in Water and Food Samples Using Artificial Neural Networks Coupled Bees Algorithm.

Bulletin of environmental contamination and toxicology
A multivariate method based on solvent terminated dispersive liquid-liquid microextraction was developed for the determination of Cu ions in aqueous samples. In the proposed approach, di-2-ethylhexylphosphoric acid, xylene and acetone were used as ch...

A mixed-scale dense convolutional neural network for image analysis.

Proceedings of the National Academy of Sciences of the United States of America
Deep convolutional neural networks have been successfully applied to many image-processing problems in recent works. Popular network architectures often add additional operations and connections to the standard architecture to enable training deeper ...