AIMC Topic: Support Vector Machine

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Epileptic seizure detection in EEG signal using machine learning techniques.

Australasian physical & engineering sciences in medicine Dec 20, 2017
Epilepsy is a well-known nervous system disorder characterized by seizures. Electroencephalograms (EEGs), which capture brain neural activity, can detect epilepsy. Traditional methods for analyzing an EEG signal for epileptic seizure detection are ti...
Humans Machine Learning Principal Component Analysis Electroencephalography Support Vector Machine Signal Processing, Computer-Assisted Epilepsy Seizures
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Automatic schizophrenic discrimination on fNIRS by using complex brain network analysis and SVM.

BMC medical informatics and decision making Dec 20, 2017
BACKGROUND: Schizophrenia is a kind of serious mental illness. Due to the lack of an objective physiological data supporting and a unified data analysis method, doctors can only rely on the subjective experience of the data to distinguish normal peop...
Support Vector Machine Schizophrenia Prefrontal Cortex Functional Neuroimaging Male Humans Female Spectroscopy, Near-Infrared Biomarkers Young Adult Adult
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Accurate and fast feature selection workflow for high-dimensional omics data.

PloS one Dec 20, 2017
We are moving into the age of 'Big Data' in biomedical research and bioinformatics. This trend could be encapsulated in this simple formula: D = S * F, where the volume of data generated (D) increases in both dimensions: the number of samples (S) and...
Support Vector Machine Principal Component Analysis Genomics Databases as Topic Multivariate Analysis Workflow Humans Algorithms
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An improved wrapper-based feature selection method for machinery fault diagnosis.

PloS one Dec 20, 2017
A major issue of machinery fault diagnosis using vibration signals is that it is over-reliant on personnel knowledge and experience in interpreting the signal. Thus, machine learning has been adapted for machinery fault diagnosis. The quantity and qu...
Equipment Failure Analysis Algorithms Support Vector Machine
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Identification of the functional alteration signatures across different cancer types with support vector machine and feature analysis.

Biochimica et biophysica acta. Molecular basis of disease Dec 19, 2017
Cancers are regarded as malignant proliferations of tumor cells present in many tissues and organs, which can severely curtail the quality of human life. The potential of using plasma DNA for cancer detection has been widely recognized, leading to th...
Humans Genes, Neoplasm Support Vector Machine DNA, Neoplasm Neoplasms Gene Ontology Gene Expression Regulation, Neoplastic
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A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data.

BMC bioinformatics Dec 19, 2017
BACKGROUND: Stratification of patient subpopulations that respond favorably to treatment or experience and adverse reaction is an essential step toward development of new personalized therapies and diagnostics. It is currently feasible to generate om...
Support Vector Machine Gene Expression Regulation Gene Regulatory Networks Models, Theoretical Humans Neural Networks, Computer Phenotype Reproducibility of Results
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Epileptic Seizures Prediction Using Machine Learning Methods.

Computational and mathematical methods in medicine Dec 19, 2017
Epileptic seizures occur due to disorder in brain functionality which can affect patient's health. Prediction of epileptic seizures before the beginning of the onset is quite useful for preventing the seizure by medication. Machine learning technique...
Seizures Diagnosis, Computer-Assisted Brain Electroencephalography Signal Processing, Computer-Assisted Reproducibility of Results Support Vector Machine Epilepsy Humans Sensitivity and Specificity Models, Statistical Algorithms
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Epileptic seizure detection using DWT-based approximate entropy, Shannon entropy and support vector machine: a case study.

Journal of medical engineering & technology Dec 18, 2017
In this work, we have used a time-frequency domain analysis method called discrete wavelet transform (DWT) technique. This method stand out compared to other proposed methods because of its algorithmic elegance and accuracy. A wavelet is a mathematic...
Epilepsy Support Vector Machine Humans Wavelet Analysis Algorithms Electroencephalography Entropy
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Symtosis: A liver ultrasound tissue characterization and risk stratification in optimized deep learning paradigm.

Computer methods and programs in biomedicine Dec 16, 2017
Background and Objective Fatty Liver Disease (FLD) - a disease caused by deposition of fat in liver cells, is predecessor to terminal diseases such as liver cancer. The machine learning (ML) techniques applied for FLD detection and risk stratificatio...
Support Vector Machine Humans Benchmarking Image Interpretation, Computer-Assisted Reproducibility of Results Fatty Liver Diagnosis, Computer-Assisted Ultrasonography Neural Networks, Computer Risk Factors Computational Biology ROC Curve Machine Learning
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Modeling the control of the central nervous system over the cardiovascular system using support vector machines.

Computers in biology and medicine Dec 15, 2017
The control of the central nervous system (CNS) over the cardiovascular system (CS) has been modeled using different techniques, such as fuzzy inductive reasoning, genetic fuzzy systems, neural networks, and nonlinear autoregressive techniques; the r...
Humans Cardiovascular System Models, Cardiovascular Models, Neurological Central Nervous System Support Vector Machine
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