Wavelet applications in medicine
IEEE Spectrum
SVM binary classifier ensembles for image classification
Proceedings of the tenth international conference on Information and knowledge management
Comparative Exudate Classification Using Support Vector Machines and Neural Networks
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part II
Fuzzy least squares support vector machines for multiclass problems
Neural Networks - 2003 Special issue: Advances in neural networks research IJCNN'03
Entropy-based algorithms for best basis selection
IEEE Transactions on Information Theory - Part 2
Expert Systems with Applications: An International Journal
Computers in Biology and Medicine
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Heart sound classification using wavelet transform and incremental self-organizing map
Digital Signal Processing
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Using combination of support vector machines for automatic analog modulation recognition
Expert Systems with Applications: An International Journal
Diagnosis of valvular heart disease through neural networks ensembles
Computer Methods and Programs in Biomedicine
Computers in Biology and Medicine
Expert Systems with Applications: An International Journal
Support Vectors Machine-based identification of heart valve diseases using heart sounds
Computer Methods and Programs in Biomedicine
Feature determination for heart sounds based on divergence analysis
Digital Signal Processing
A new intelligent diagnosis system for the heart valve diseases by using genetic-SVM classifier
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Effects of discretization on determination of coronary artery disease using support vector machine
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Expert Systems with Applications: An International Journal
Evaluation of ensemble methods for diagnosing of valvular heart disease
Expert Systems with Applications: An International Journal
A comparative study of DWT, CWT and DCT transformations in ECG arrhythmias classification
Expert Systems with Applications: An International Journal
A learning method for the class imbalance problem with medical data sets
Computers in Biology and Medicine
An automatic diagnosis system based on thyroid gland: ADSTG
Expert Systems with Applications: An International Journal
A decision making system to automatic recognize of traffic accidents on the basis of a GIS platform
Expert Systems with Applications: An International Journal
Automatic phonocardiograph signal analysis for detecting heart valve disorders
Expert Systems with Applications: An International Journal
An automatic diabetes diagnosis system based on LDA-Wavelet Support Vector Machine Classifier
Expert Systems with Applications: An International Journal
Short communication: A new intelligent hepatitis diagnosis system: PCA-LSSVM
Expert Systems with Applications: An International Journal
A New Expert System for Diagnosis of Lung Cancer: GDA--LS_SVM
Journal of Medical Systems
Design of a Fuzzy-based Decision Support System for Coronary Heart Disease Diagnosis
Journal of Medical Systems
Automatic RNA virus classification using the Entropy-ANFIS method
Digital Signal Processing
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In this paper, a decision support system that classifies the Doppler signals of the heart valve to two classes (normal and abnormal) is presented to support the cardiologist. The paper uses our previous paper where ANN is used as a classifier, as feature extractor from measured Doppler signal. To make this, it uses wavelet transforms and short time Fourier transform methods. Before it classifies these features, it applies Wavelet entropy to them. In this paper, our aim is to develop our previous work by using least-squares support vector machine (LS-SVM) classifier instead of ANN. We use LS-SVM and backpropagation artificial neural network (BP-ANN) to classify the extracted features. In addition, we use receiver operator characteristic (ROC) curves to compare sensitivities and specificities of these classifiers and compute the area under the curves. Finally, we evaluate two classifiers in all aspects.