Search results for "Feature reduction"

showing 2 items of 2 documents

Evaluation of a Support Vector Machine Based Method for Crohn’s Disease Classification

2019

Crohn’s disease (CD) is a chronic, disabling inflammatory bowel disease that affects millions of people worldwide. CD diagnosis is a challenging issue that involves a combination of radiological, endoscopic, histological, and laboratory investigations. Medical imaging plays an important role in the clinical evaluation of CD. Enterography magnetic resonance imaging (E-MRI) has been proven to be a useful diagnostic tool for disease activity assessment. However, the manual classification process by expert radiologists is time-consuming and expensive. This paper proposes the evaluation of an automatic Support Vector Machine (SVM) based supervised learning method for CD classification. A real E-…

Crohn's diseasemedicine.diagnostic_testComputer sciencebusiness.industryFeature vectorFeature extractionSupervised learningMagnetic resonance imagingPattern recognitionmedicine.diseaseCrohn’s disease classification Feature extraction Feature reduction K-fold cross-validation Supervised learning Support vector machinesSupport vector machinemedicineMedical imagingArtificial intelligencebusinessReliability (statistics)
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A Novel System for Multi-level Crohn’s Disease Classification and Grading Based on a Multiclass Support Vector Machine

2020

Crohn’s disease (CD) is a chronic inflammatory condition of the gastrointestinal tract that can highly alter patient’s quality of life. Diagnostic imaging, such as Enterography Magnetic Resonance Imaging (E-MRI), provides crucial information for CD activity assessment. Automatic learning methods play a fundamental role in the classification of CD and allow to avoid the long and expensive manual classification process by radiologists. This paper presents a novel classification method that uses a multiclass Support Vector Machine (SVM) based on a Radial Basis Function (RBF) kernel for the grading of CD inflammatory activity. To validate the system, we have used a dataset composed of 800 E-MRI…

Hyperparameterbusiness.industryComputer scienceMulticlass support vector machineBayesian optimizationSupervised learningFeature extractionFeature reductionCrohn’s disease multi-level classification and gradingK-fold cross-validationPattern recognitionSupport vector machineRadial basis function kernelMedical imagingFeature extractionArtificial intelligencebusinessClassifier (UML)Supervised learningBayesian optimization
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