AIMC Topic: Support Vector Machine

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A novel gene selection algorithm for cancer classification using microarray datasets.

BMC medical genomics Jan 15, 2019
BACKGROUND: Microarray datasets are an important medical diagnostic tool as they represent the states of a cell at the molecular level. Available microarray datasets for classifying cancer types generally have a fairly small sample size compared to t...
Mutation Neoplasms Computational Biology Oligonucleotide Array Sequence Analysis Support Vector Machine Gene Expression Profiling Genes, Neoplasm
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Automatic lung nodule detection using multi-scale dot nodule-enhancement filter and weighted support vector machines in chest computed tomography.

PloS one Jan 10, 2019
A novel CAD scheme for automated lung nodule detection is proposed to assist radiologists with the detection of lung cancer on CT scans. The proposed scheme is composed of four major steps: (1) lung volume segmentation, (2) nodule candidate extractio...
Humans False Positive Reactions Algorithms Support Vector Machine Tomography, X-Ray Computed Imaging, Three-Dimensional Lung Lung Neoplasms Solitary Pulmonary Nodule
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A proposal of prior probability-oriented clustering in feature encoding strategies.

PloS one Jan 10, 2019
Codebook-based feature encodings are a standard framework for image recognition issues. A codebook is usually constructed by clusterings, such as the k-means and the Gaussian Mixture Model (GMM). A codebook size is an important factor to decide the t...
Image Processing, Computer-Assisted Support Vector Machine Cluster Analysis Datasets as Topic Probability Pattern Recognition, Automated
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A review on machine learning methods for in silico toxicity prediction.

Journal of environmental science and health. Part C, Environmental carcinogenesis & ecotoxicology reviews Jan 10, 2019
In silico toxicity prediction plays an important role in the regulatory decision making and selection of leads in drug design as in vitro/vivo methods are often limited by ethics, time, budget, and other resources. Many computational methods have bee...
Machine Learning Support Vector Machine Toxicity Tests Environmental Pollutants Algorithms Quantitative Structure-Activity Relationship Computer Simulation
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Machine learning models for predicting endocrine disruption potential of environmental chemicals.

Journal of environmental science and health. Part C, Environmental carcinogenesis & ecotoxicology reviews Jan 10, 2019
We introduce here ML4Tox, a framework offering Deep Learning and Support Vector Machine models to predict agonist, antagonist, and binding activities of chemical compounds, in this case for the estrogen receptor ligand-binding domain. The ML4Tox mode...
Toxicity Tests Endocrine Disruptors Receptors, Estrogen Machine Learning Environmental Pollutants Protein Binding Computer Simulation Quantitative Structure-Activity Relationship Support Vector Machine
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Support vector machine-based multivariate pattern classification of methamphetamine dependence using arterial spin labeling.

Addiction biology Jan 9, 2019
Arterial spin labeling (ASL) magnetic resonance imaging has been widely applied to identify cerebral blood flow (CBF) abnormalities in a number of brain disorders. To evaluate its significance in detecting methamphetamine (MA) dependence, this study ...
Perfusion Imaging Spin Labels Imaging, Three-Dimensional Support Vector Machine Magnetic Resonance Imaging Amphetamine-Related Disorders Cerebrovascular Circulation Area Under Curve Adult Methamphetamine Male Case-Control Studies ROC Curve Humans Brain Young Adult
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Qoala-T: A supervised-learning tool for quality control of FreeSurfer segmented MRI data.

NeuroImage Jan 8, 2019
Performing quality control to detect image artifacts and data-processing errors is crucial in structural magnetic resonance imaging, especially in developmental studies. Currently, many studies rely on visual inspection by trained raters for quality ...
Magnetic Resonance Imaging Quality Control Datasets as Topic Human Development Neuroimaging Humans Conduct Disorder Autism Spectrum Disorder Adult Brain Adolescent Sensitivity and Specificity Support Vector Machine Young Adult Child Cross-Sectional Studies Longitudinal Studies
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Performance of machine-learning algorithms to pattern recognition and classification of hearing impairment in Brazilian farmers exposed to pesticide and/or cigarette smoke.

Environmental science and pollution research international Jan 8, 2019
The use of pesticides has been increasing in agriculture, leading to a public health problem. The aim of this study was to evaluate ototoxic effects in farmers who were exposed to cigarette smoke and/or pesticides and to identify possible classificat...
Machine Learning Algorithms Female Aged Humans Brazil Adolescent Occupational Exposure Support Vector Machine Young Adult Adult Male Farmers Pesticides Hearing Loss Nicotiana Smoking Air Pollutants, Occupational Tobacco Smoke Pollution
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An Intelligent Sleep Apnea Classification System Based on EEG Signals.

Journal of medical systems Jan 8, 2019
Sleep Apnea is a sleep disorder which causes stop in breathing for a short duration of time that happens to human beings and animals during sleep. Electroencephalogram (EEG) plays a vital role in detecting the sleep apnea by sensing and recording the...
Humans Neural Networks, Computer Machine Learning Adult Electroencephalography Signal Processing, Computer-Assisted Sleep Apnea Syndromes Polysomnography Male Middle Aged Support Vector Machine
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DeepCDpred: Inter-residue distance and contact prediction for improved prediction of protein structure.

PloS one Jan 8, 2019
Rapid, accurate prediction of protein structure from amino acid sequence would accelerate fields as diverse as drug discovery, synthetic biology and disease diagnosis. Massively improved prediction of protein structures has been driven by improving t...
Amino Acid Sequence Protein Structure, Tertiary Sequence Analysis, Protein Algorithms Deep Learning Computational Biology Databases, Protein Models, Molecular Support Vector Machine Proteins
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