AIMC Topic: Support Vector Machine

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Robust Support Matrix Machine for Single Trial EEG Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Mar 1, 2018
Electroencephalogram (EEG) signals are of complex structure and can be naturally represented as matrices. Classification is one of the most important steps for EEG signal processing. Newly developed classifiers can handle these matrix-form data by ad...
Humans Software Algorithms Artifacts Brain-Computer Interfaces Signal-To-Noise Ratio Support Vector Machine Electroencephalography Signal Processing, Computer-Assisted
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Hybrid gray wolf optimizer-artificial neural network classification approach for magnetic resonance brain images.

Applied optics Mar 1, 2018
Automated and accurate classification of magnetic resonance images (MRIs) of the brain has great importance for medical analysis and interpretation. This paper presents a hybrid optimized classification method to classify the brain tumor by classifyi...
Humans Neural Networks, Computer Machine Learning Magnetic Resonance Imaging Models, Theoretical Algorithms Support Vector Machine Pattern Recognition, Automated Brain Brain Diseases
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[Design and Implementation of Portable Abnormal ECG Signal Analysis Instrument Based on Feature Classifcation].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation Feb 8, 2018
OBJECTIVES: To collect and analyze the ECG signal in real time, the analog filter and the signal amplifier were used to construct the abnormal signal acquisition and classification system.
Arrhythmias, Cardiac Support Vector Machine Signal Processing, Computer-Assisted Heart Humans Algorithms Electrocardiography
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Prostate cancer detection using machine learning techniques by employing combination of features extracting strategies.

Cancer biomarkers : section A of Disease markers Feb 6, 2018
Prostate is a second leading causes of cancer deaths among men. Early detection of cancer can effectively reduce the rate of mortality caused by Prostate cancer. Due to high and multiresolution of MRIs from prostate cancer require a proper diagnostic...
Humans Machine Learning Bayes Theorem Prostatic Neoplasms Male Support Vector Machine
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Inferring imagined speech using EEG signals: a new approach using Riemannian manifold features.

Journal of neural engineering Feb 1, 2018
OBJECTIVE: In this paper, we investigate the suitability of imagined speech for brain-computer interface (BCI) applications.
Adult Male Speech Humans Female Young Adult Imagination Support Vector Machine Electroencephalography Brain-Computer Interfaces
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In silico Prediction of Inhibitory Constant of Thrombin Inhibitors Using Machine Learning.

Combinatorial chemistry & high throughput screening Jan 1, 2018
BACKGROUND: Thrombin is the central protease of the vertebrate blood coagulation cascade, which is closely related to cardiovascular diseases. The inhibitory constant Ki is the most significant property of thrombin inhibitors.
Models, Molecular Molecular Structure Drug Discovery Humans Quantitative Structure-Activity Relationship Linear Models Thrombin Support Vector Machine Thermodynamics Machine Learning Anticoagulants Computer Simulation
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A Network Integration Method for Deciphering the Types of Metabolic Pathway of Chemicals with Heterogeneous Information.

Combinatorial chemistry & high throughput screening Jan 1, 2018
AIM AND OBJECTIVE: A metabolic pathway is an important type of biological pathway, which is composed of a series of chemical reactions. It provides essential molecules and energies for living organisms. To date, several metabolic pathways have been u...
Metabolic Networks and Pathways Organic Chemicals Models, Molecular Molecular Structure Computational Biology Support Vector Machine Structure-Activity Relationship
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Predicting Inhibitors for Multidrug Resistance Associated Protein-2 Transporter by Machine Learning Approach.

Combinatorial chemistry & high throughput screening Jan 1, 2018
BACKGROUND: The efflux transporter multidrug resistance associated protein-2 belongs to ATP-binding cassette superfamily which plays an important role in multidrug resistance and drugdrug interactions. Efflux transporters are considered to be importa...
Multidrug Resistance-Associated Proteins Multidrug Resistance-Associated Protein 2 Support Vector Machine Machine Learning Molecular Structure Quantitative Structure-Activity Relationship Algorithms Drug Discovery Databases, Pharmaceutical
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Machine-Learning Prediction of Drug-Induced Cardiac Arrhythmia: Analysis of Gene Expression and Clustering.

Critical reviews in biomedical engineering Jan 1, 2018
A marked delay in the electrical repolarization of heart ventricles is characterized by prolongation of the Q-T wave (QT) interval on a surface electrocardiogram. Such a delay can lead to potentially life-threatening cardiac arrhythmia (torsades de p...
Sensitivity and Specificity Animals Male Mice Rats Drug Design Gene Expression Profiling Machine Learning Female Reproducibility of Results Humans Heart Ventricles Arrhythmias, Cardiac MAP Kinase Signaling System False Positive Reactions Gene Expression Regulation Electrocardiography Torsades de Pointes Clinical Trials as Topic Support Vector Machine Signal Processing, Computer-Assisted Cluster Analysis Heart Drug Evaluation, Preclinical
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Research: Use of Dry Electroencephalogram and Support Vector for Objective Pain Assessment.

Biomedical instrumentation & technology Jan 1, 2018
The reliability of normal gel-based electrode electroencephalogram (EEG) for measuring pain has been validated. To date, however, few documented trials have used dry EEG for pain quantification. The primary goal of this study was to objectively quant...
Humans Female Young Adult Support Vector Machine Adult Pain Measurement Male Cohort Studies Electroencephalography Signal Processing, Computer-Assisted
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