AIMC Topic: Pattern Recognition, Automated

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Segmentation of Fetal Left Ventricle in Echocardiographic Sequences Based on Dynamic Convolutional Neural Networks.

IEEE transactions on bio-medical engineering
Segmentation of fetal left ventricle (LV) in echocardiographic sequences is important for further quantitative analysis of fetal cardiac function. However, image gross inhomogeneities and fetal random movements make the segmentation a challenging pro...

An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy.

PloS one
For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is o...

Machine Learning for Characterization of Insect Vector Feeding.

PLoS computational biology
Insects that feed by ingesting plant and animal fluids cause devastating damage to humans, livestock, and agriculture worldwide, primarily by transmitting pathogens of plants and animals. The feeding processes required for successful pathogen transmi...

Universal Feature Extraction for Traffic Identification of the Target Category.

PloS one
Traffic identification of the target category is currently a significant challenge for network monitoring and management. To identify the target category with pertinence, a feature extraction algorithm based on the subset with highest proportion is p...

Causality patterns and machine learning for the extraction of problem-action relations in discharge summaries.

International journal of medical informatics
Clinical narrative text includes information related to a patient's medical history such as chronological progression of medical problems and clinical treatments. A chronological view of a patient's history makes clinical audits easier and improves q...

Automatic detection and classification of leukocytes using convolutional neural networks.

Medical & biological engineering & computing
The detection and classification of white blood cells (WBCs, also known as Leukocytes) is a hot issue because of its important applications in disease diagnosis. Nowadays the morphological analysis of blood cells is operated manually by skilled opera...

Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments.

PLoS computational biology
Live-cell imaging has opened an exciting window into the role cellular heterogeneity plays in dynamic, living systems. A major critical challenge for this class of experiments is the problem of image segmentation, or determining which parts of a micr...

Automatic Valve Plane Localization in Myocardial Perfusion SPECT/CT by Machine Learning: Anatomic and Clinical Validation.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Precise definition of the mitral valve plane (VP) during segmentation of the left ventricle for SPECT myocardial perfusion imaging (MPI) quantification often requires manual adjustment, which affects the quantification of perfusion. We developed a ma...

WORMHOLE: Novel Least Diverged Ortholog Prediction through Machine Learning.

PLoS computational biology
The rapid advancement of technology in genomics and targeted genetic manipulation has made comparative biology an increasingly prominent strategy to model human disease processes. Predicting orthology relationships between species is a vital componen...

Mammogram Enhancement Using Intuitionistic Fuzzy Sets.

IEEE transactions on bio-medical engineering
OBJECTIVE: Conventional mammogram enhancement methods use transform-domain filtering, which possibly produce some artifacts or not well highlight all local details in images. This paper presents a new enhancement method based on intuitionistic fuzzy ...