AIMC Topic: Pattern Recognition, Automated

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Chemical named entity recognition in patents by domain knowledge and unsupervised feature learning.

Database : the journal of biological databases and curation
Medicinal chemistry patents contain rich information about chemical compounds. Although much effort has been devoted to extracting chemical entities from scientific literature, limited numbers of patent mining systems are publically available, probab...

Respiratory Artefact Removal in Forced Oscillation Measurements: A Machine Learning Approach.

IEEE transactions on bio-medical engineering
GOAL: Respiratory artefact removal for the forced oscillation technique can be treated as an anomaly detection problem. Manual removal is currently considered the gold standard, but this approach is laborious and subjective. Most existing automated t...

Improvements on ν-Twin Support Vector Machine.

Neural networks : the official journal of the International Neural Network Society
In this paper, we propose two novel binary classifiers termed as "Improvements on ν-Twin Support Vector Machine: Iν-TWSVM and Iν-TWSVM (Fast)" that are motivated by ν-Twin Support Vector Machine (ν-TWSVM). Similar to ν-TWSVM, Iν-TWSVM determines two ...

Monitoring of total positive end-expiratory pressure during mechanical ventilation by artificial neural networks.

Journal of clinical monitoring and computing
Ventilation treatment of acute lung injury (ALI) requires the application of positive airway pressure at the end of expiration (PEEP) to avoid lung collapse. However, the total pressure exerted on the alveolar walls (PEEP) is the sum of PEEP and intr...

Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks.

NeuroImage
Feedforward deep neural networks (DNNs), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the succes...

A Computational Framework for Realistic Retina Modeling.

International journal of neural systems
Computational simulations of the retina have led to valuable insights about the biophysics of its neuronal activity and processing principles. A great number of retina models have been proposed to reproduce the behavioral diversity of the different v...

Improve Glioblastoma Multiforme Prognosis Prediction by Using Feature Selection and Multiple Kernel Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Glioblastoma multiforme (GBM) is a highly aggressive type of brain cancer with very low median survival. In order to predict the patient's prognosis, researchers have proposed rules to classify different glioma cancer cell subtypes. However, survival...

Pattern recognition for electroencephalographic signals based on continuous neural networks.

Neural networks : the official journal of the International Neural Network Society
This study reports the design and implementation of a pattern recognition algorithm to classify electroencephalographic (EEG) signals based on artificial neural networks (NN) described by ordinary differential equations (ODEs). The training method fo...

Ensembles of Deep Learning Architectures for the Early Diagnosis of the Alzheimer's Disease.

International journal of neural systems
Computer Aided Diagnosis (CAD) constitutes an important tool for the early diagnosis of Alzheimer's Disease (AD), which, in turn, allows the application of treatments that can be simpler and more likely to be effective. This paper explores the constr...

Automated assessment of thigh composition using machine learning for Dixon magnetic resonance images.

Magma (New York, N.Y.)
OBJECTIVES: To develop and validate a machine learning based automated segmentation method that jointly analyzes the four contrasts provided by Dixon MRI technique for improved thigh composition segmentation accuracy.