AIMC Topic: Neural Networks, Computer

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Stability analysis of Cohen-Grossberg neural networks of neutral-type: Multiple delays case.

Neural networks : the official journal of the International Neural Network Society
The essential purpose of this work is to conduct an investigation into stability problem for the class of neutral-type Cohen-Grossberg neural networks including multiple time delays in states and multiple neutral delays in time derivative of states. ...

The use of artificial neural network analysis can improve the risk-stratification of patients presenting with suspected deep vein thrombosis.

British journal of haematology
Artificial neural networks are machine-learning algorithms designed to analyse data without a pre-existing hypothesis as to any associations that may exist. This technique has not previously been applied to the risk stratification of patients referre...

DeepPVP: phenotype-based prioritization of causative variants using deep learning.

BMC bioinformatics
BACKGROUND: Prioritization of variants in personal genomic data is a major challenge. Recently, computational methods that rely on comparing phenotype similarity have shown to be useful to identify causative variants. In these methods, pathogenicity ...

Detecting Potential Adverse Drug Reactions Using a Deep Neural Network Model.

Journal of medical Internet research
BACKGROUND: Adverse drug reactions (ADRs) are common and are the underlying cause of over a million serious injuries and deaths each year. The most familiar method to detect ADRs is relying on spontaneous reports. Unfortunately, the low reporting rat...

Multi-Information Flow CNN and Attribute-Aided Reranking for Person Reidentification.

Computational intelligence and neuroscience
This paper presents a multi-information flow convolutional neural network (MiF-CNN) model for person reidentification (re-id). It contains several specific multilayer convolutional structures, where the input and output of a convolutional layer are c...

A Greedy Assist-as-Needed Controller for Upper Limb Rehabilitation.

IEEE transactions on neural networks and learning systems
Previous studies on robotic rehabilitation have shown that subjects' active participation and effort involved in rehabilitation training can promote the performance of therapies. In order to improve the voluntary effort of participants during the reh...

Attention gated networks: Learning to leverage salient regions in medical images.

Medical image analysis
We propose a novel attention gate (AG) model for medical image analysis that automatically learns to focus on target structures of varying shapes and sizes. Models trained with AGs implicitly learn to suppress irrelevant regions in an input image whi...

RAMS: Remote and automatic mammogram screening.

Computers in biology and medicine
About one in eight women in the U.S. will develop invasive breast cancer at some point in life. Breast cancer is the most common cancer found in women and if it is identified at an early stage by the use of mammograms, x-ray images of the breast, the...

Estimation of fungal biomass using multiphase artificial neural network based dynamic soft sensor.

Journal of microbiological methods
Interest in low cost cellulase production has become a major challenge in recent years for biorefineries. Fed-batch fermentation of Trichoderma strains for the production of low cost cellulase is carried out on complex media that has various soluble ...

Stock Market Forecasting Using Restricted Gene Expression Programming.

Computational intelligence and neuroscience
Stock index prediction is considered as a difficult task in the past decade. In order to predict stock index accurately, this paper proposes a novel prediction method based on S-system model. Restricted gene expression programming (RGEP) is proposed ...