AIMC Topic: Pattern Recognition, Automated

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Classifier transfer with data selection strategies for online support vector machine classification with class imbalance.

Journal of neural engineering Feb 13, 2017
OBJECTIVE: Classifier transfers usually come with dataset shifts. To overcome dataset shifts in practical applications, we consider the limitations in computational resources in this paper for the adaptation of batch learning algorithms, like the sup...
Algorithms Brain Computer Simulation Reproducibility of Results Sensitivity and Specificity Humans Pattern Recognition, Automated Brain-Computer Interfaces Online Systems Support Vector Machine Models, Neurological Electroencephalography Data Mining
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Separating generalized anxiety disorder from major depression using clinical, hormonal, and structural MRI data: A multimodal machine learning study.

Brain and behavior Feb 12, 2017
BACKGROUND: Generalized anxiety disorder (GAD) is difficult to recognize and hard to separate from major depression (MD) in clinical settings. Biomarkers might support diagnostic decisions. This study used machine learning on multimodal biobehavioral...
Pattern Recognition, Automated Gray Matter White Matter Female Young Adult Adult Male Support Vector Machine Magnetic Resonance Imaging Hydrocortisone Depressive Disorder, Major Humans Anxiety Disorders
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Adaptive low-rank subspace learning with online optimization for robust visual tracking.

Neural networks : the official journal of the International Neural Network Society Feb 10, 2017
In recent years, sparse and low-rank models have been widely used to formulate appearance subspace for visual tracking. However, most existing methods only consider the sparsity or low-rankness of the coefficients, which is not sufficient enough for ...
Humans Artificial Intelligence Algorithms Models, Theoretical Pattern Recognition, Automated
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Structured Pyramidal Neural Networks.

International journal of neural systems Feb 9, 2017
The Pyramidal Neural Networks (PNN) are an example of a successful recently proposed model inspired by the human visual system and deep learning theory. PNNs are applied to computer vision and based on the concept of receptive fields. This paper prop...
Pyramidal Cells Humans Neural Networks, Computer Visual Pathways Female Male Support Vector Machine Area Under Curve Time Factors Models, Neurological Pattern Recognition, Automated ROC Curve Blood Cells Image Processing, Computer-Assisted
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Classification of nervous system withdrawn and approved drugs with ToxPrint features via machine learning strategies.

Computer methods and programs in biomedicine Feb 9, 2017
BACKGROUND AND OBJECTIVES: Early-phase virtual screening of candidate drug molecules plays a key role in pharmaceutical industry from data mining and machine learning to prevent adverse effects of the drugs. Computational classification methods can d...
Support Vector Machine Carbon Area Under Curve Drug Monitoring Toluene Linear Models Pattern Recognition, Automated Pharmaceutical Preparations Data Mining Nervous System False Positive Reactions Patient Safety Ethylamines Computer Simulation Drug Approval Safety-Based Drug Withdrawals Sensitivity and Specificity Risk Benzene Humans Product Surveillance, Postmarketing Algorithms
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Automated diagnosis of congestive heart failure using dual tree complex wavelet transform and statistical features extracted from 2s of ECG signals.

Computers in biology and medicine Feb 7, 2017
Identification of alarming features in the electrocardiogram (ECG) signal is extremely significant for the prediction of congestive heart failure (CHF). ECG signal analysis carried out using computer-aided techniques can speed up the diagnosis proces...
Pattern Recognition, Automated Wavelet Analysis Electrocardiography Models, Statistical Data Interpretation, Statistical Heart Failure Reproducibility of Results Aged Aged, 80 and over Young Adult Male Middle Aged Diagnosis, Computer-Assisted Adult Sensitivity and Specificity Machine Learning Algorithms Computer Simulation Female Humans
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Artificial neural networks predict the incidence of portosplenomesenteric venous thrombosis in patients with acute pancreatitis.

Journal of thrombosis and haemostasis : JTH Feb 3, 2017
UNLABELLED: Essentials Predicting the occurrence of portosplenomesenteric vein thrombosis (PSMVT) is difficult. We studied 72 patients with acute pancreatitis. Artificial neural networks modeling was more accurate than logistic regression in predicti...
Female Aged Young Adult Adult Male Humans Neural Networks, Computer Software Retrospective Studies Regression Analysis Acute Disease Pattern Recognition, Automated Ultrasonography, Doppler Pancreatitis Middle Aged ROC Curve Logistic Models Venous Thrombosis
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Insect Bio-inspired Neural Network Provides New Evidence on How Simple Feature Detectors Can Enable Complex Visual Generalization and Stimulus Location Invariance in the Miniature Brain of Honeybees.

PLoS computational biology Feb 3, 2017
The ability to generalize over naturally occurring variation in cues indicating food or predation risk is highly useful for efficient decision-making in many animals. Honeybees have remarkable visual cognitive abilities, allowing them to classify vis...
Brain Computer Simulation Animals Models, Neurological Pattern Recognition, Automated Nerve Net Pattern Recognition, Visual Biomimetics Bees Neural Networks, Computer
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Performance of a Machine Learning Classifier of Knee MRI Reports in Two Large Academic Radiology Practices: A Tool to Estimate Diagnostic Yield.

AJR. American journal of roentgenology Jan 31, 2017
OBJECTIVE: The purpose of this study is to evaluate the performance of a natural language processing (NLP) system in classifying a database of free-text knee MRI reports at two separate academic radiology practices.
Knee California Radiology Information Systems North Carolina Radiology Department, Hospital Sensitivity and Specificity Support Vector Machine Magnetic Resonance Imaging Humans Academic Medical Centers Natural Language Processing Workload Machine Learning Pattern Recognition, Automated Data Mining Reproducibility of Results Image Enhancement
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A Theoretical Analysis of Why Hybrid Ensembles Work.

Computational intelligence and neuroscience Jan 31, 2017
Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithm...
Pattern Recognition, Automated Humans Artificial Intelligence Algorithms Bayes Theorem
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