AIMC Topic: Neural Networks, Computer

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Translating from Proteins to Ribonucleic Acids for Ligand-binding Site Detection.

Molecular informatics
Identifying druggable ligand-binding sites on the surface of the macromolecular targets is an important process in structure-based drug discovery. Deep-learning models have been shown to successfully predict ligand-binding sites of proteins. As a ste...

CapsProm: a capsule network for promoter prediction.

Computers in biology and medicine
Locating the promoter region in DNA sequences is of paramount importance in bioinformatics. This problem has been widely studied in the literature, but it has not yet been fully resolved. Some researchers have shown remarkable results using convoluti...

A metric learning-based method using graph neural network for pancreatic cystic neoplasm classification from CTs.

Medical physics
PURPOSE: Pancreatic cystic neoplasms (PCNs) are relatively rare neoplasms and difficult to be classified preoperatively. Ordinary deep learning methods have great potential to provide support for doctors in PCNs classification but require a quantity ...

The Hemodynamic Parameters Values Prediction on the Non-Invasive Hydrocuff Technology Basis with a Neural Network Applying.

Sensors (Basel, Switzerland)
The task to develop a mechanism for predicting the hemodynamic parameters values based on non-invasive hydrocuff technology of a pulse wave signal fixation is described in this study. The advantages and disadvantages of existing methods of recording ...

Evaluation of 1D and 2D Deep Convolutional Neural Networks for Driving Event Recognition.

Sensors (Basel, Switzerland)
Driving event detection and driver behavior recognition have been widely explored for many purposes, including detecting distractions, classifying driver actions, detecting kidnappings, pricing vehicle insurance, evaluating eco-driving, and managing ...

A Novel Lightweight Anonymous Proxy Traffic Detection Method Based on Spatio-Temporal Features.

Sensors (Basel, Switzerland)
Anonymous proxies are used by criminals for illegal network activities due to their anonymity, such as data theft and cyber attacks. Therefore, anonymous proxy traffic detection is very essential for network security. In recent years, detection based...

Machine-learning-assisted molecular design of phenylnaphthylamine-type antioxidants.

Physical chemistry chemical physics : PCCP
In this study, a total of 302 molecular structures of phenylnaphthylamine antioxidants based on -phenyl-1-naphthylamine and -phenyl-2-naphthylamine skeletons with various substituents were modeled by exhaustive methods. Antioxidant parameters, includ...

Representing globally accurate reactive potential energy surfaces with complex topography by combining Gaussian process regression and neural networks.

Physical chemistry chemical physics : PCCP
There has been increasing attention in using machine learning technologies, such as neural networks (NNs) and Gaussian process regression (GPR), to model multi-dimensional potential energy surfaces (PESs). A PES constructed using NNs features high ac...

Deep Graph Learning for Anomalous Citation Detection.

IEEE transactions on neural networks and learning systems
Anomaly detection is one of the most active research areas in various critical domains, such as healthcare, fintech, and public security. However, little attention has been paid to scholarly data, that is, anomaly detection in a citation network. Cit...

Data-Driven Deep Supervision for Medical Image Segmentation.

IEEE transactions on medical imaging
Medical image segmentation plays a vital role in disease diagnosis and analysis. However, data-dependent difficulties such as low image contrast, noisy background, and complicated objects of interest render the segmentation problem challenging. These...