AIMC Topic: Support Vector Machine

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A systematic comparison of feature space effects on disease classifier performance for phenotype identification of five diseases.

Journal of biomedical informatics Aug 1, 2015
Automated phenotype identification plays a critical role in cohort selection and bioinformatics data mining. Natural Language Processing (NLP)-informed classification techniques can robustly identify phenotypes in unstructured medical notes. In this ...
Cardiovascular Diseases Diagnosis, Computer-Assisted Decision Support Systems, Clinical Electronic Health Records Humans Phenotype Reproducibility of Results Sensitivity and Specificity Natural Language Processing Data Mining New York Diabetes Mellitus Pattern Recognition, Automated Support Vector Machine Obesity
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Extracting relations from traditional Chinese medicine literature via heterogeneous entity networks.

Journal of the American Medical Informatics Association : JAMIA Jul 29, 2015
OBJECTIVE: Traditional Chinese medicine (TCM) is a unique and complex medical system that has developed over thousands of years. This article studies the problem of automatically extracting meaningful relations of entities from TCM literature, for th...
Humans Support Vector Machine Medicine, Chinese Traditional Datasets as Topic Information Storage and Retrieval
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MATEPRED-A-SVM-Based Prediction Method for Multidrug And Toxin Extrusion (MATE) Proteins.

Computational biology and chemistry Jul 29, 2015
The growth and spread of drug resistance in bacteria have been well established in both mankind and beasts and thus is a serious public health concern. Due to the increasing problem of drug resistance, control of infectious diseases like diarrhea, pn...
Drug Resistance Organic Cation Transport Proteins Position-Specific Scoring Matrices Reproducibility of Results Support Vector Machine Amino Acids Dipeptides Hydrophobic and Hydrophilic Interactions
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Supervised machine learning-based classification scheme to segment the brainstem on MRI in multicenter brain tumor treatment context.

International journal of computer assisted radiology and surgery Jul 24, 2015
PURPOSE: To constrain the risk of severe toxicity in radiotherapy and radiosurgery, precise volume delineation of organs at risk is required. This task is still manually performed, which is time-consuming and prone to observer variability. To address...
Machine Learning Brain Neoplasms Image Processing, Computer-Assisted Support Vector Machine Magnetic Resonance Imaging Organ Size Humans Brain Stem
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High-order neural networks and kernel methods for peptide-MHC binding prediction.

Bioinformatics (Oxford, England) Jul 23, 2015
MOTIVATION: Effective computational methods for peptide-protein binding prediction can greatly help clinical peptide vaccine search and design. However, previous computational methods fail to capture key nonlinear high-order dependencies between diff...
Major Histocompatibility Complex Protein Binding Support Vector Machine Databases, Protein Amino Acid Sequence Area Under Curve Humans Algorithms Molecular Sequence Data Neural Networks, Computer Epitopes Peptides ROC Curve
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SFM: A novel sequence-based fusion method for disease genes identification and prioritization.

Journal of theoretical biology Jul 21, 2015
The identification of disease genes from human genome is of great importance to improve diagnosis and treatment of disease. Several machine learning methods have been introduced to identify disease genes. However, these methods mostly differ in the p...
Chemistry, Physical Disease Support Vector Machine Decision Trees Amino Acids Algorithms Genetic Predisposition to Disease Computational Biology Humans Models, Genetic
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Relevance Vector Machines: Sparse Classification Methods for QSAR.

Journal of chemical information and modeling Jul 21, 2015
Sparse machine learning methods have provided substantial benefits to quantitative structure property modeling, as they make model interpretation simpler and generate models with improved predictivity. Sparsity is usually induced via Bayesian regular...
Algorithms Support Vector Machine Bayes Theorem Quantitative Structure-Activity Relationship
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Exploring multifractal-based features for mild Alzheimer's disease classification.

Magnetic resonance in medicine Jul 20, 2015
PURPOSE: Multifractal applications to resting state functional MRI (rs-fMRI) time series for diagnosing Alzheimer's disease (AD) are still limited. We aim to address two issues: (I) if and what multifractal features are sufficiently discriminative to...
Pattern Recognition, Automated Image Enhancement Fractals Diagnosis, Differential Alzheimer Disease Image Interpretation, Computer-Assisted Subtraction Technique Aged Sensitivity and Specificity Male Severity of Illness Index Support Vector Machine Magnetic Resonance Imaging Brain Female Reproducibility of Results Humans Algorithms
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Discrimination of driver and passenger mutations in epidermal growth factor receptor in cancer.

Mutation research Jul 20, 2015
Cancer is one of the most life-threatening diseases and mutations in several genes are the vital cause in tumorigenesis. Protein kinases play essential roles in cancer progression and specifically, epidermal growth factor receptor (EGFR) is an import...
Mutation, Missense Models, Genetic Humans Support Vector Machine Neoplasms ErbB Receptors Polymorphism, Single Nucleotide
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Features identification for automatic burn classification.

Burns : journal of the International Society for Burn Injuries Jul 15, 2015
PURPOSE: In this paper an automatic system to diagnose burn depths based on colour digital photographs is presented.
Databases, Factual Reproducibility of Results Sensitivity and Specificity Diagnosis, Computer-Assisted Humans Algorithms Burn Units Automation Photography Trauma Severity Indices Support Vector Machine Skin Burns
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