Introduction: In this paper, a method is presented to classify the breast cancer masses according to new geometric features. Methods: After obtaining digital breast mammogram images from the digital database for screening mammography (DDSM), image preprocessing was performed. Then, by using image processing methods, an algorithm was developed for automatic extracting of masses from other norma...

Steinwart was the first to prove universal consistency of support vector machine classification. His proof analyzed the ‘standard’ support vector machine classifier, which is restricted to binary classification problems. In contrast, recent analysis has resulted in the common belief that several extensions of SVM classification to more than two classes are inconsistent. Countering this belief, ...

In this paper, we present a novel algorithm for reducing the runtime computational complexity of a Support Vector Machine classifier. This is achieved by approximating the Support Vector Machine decision function by an overcomplete Haar wavelet transformation. This provides a set of classifiers of increasing complexity that can be used in a cascaded fashion yielding excellent runtime performanc...

The electrocardiography allowed us to make a diagnosis of several cardiovascular diseases by representing the electrical activity heart over time; this representation is called electrocardiogram (ECG) signal. In study we have proposed model based on processing ECG signal wavelet decomposition using discrete transform (DWT). This firstly makes it possible denoise then extract statistical feature...

To prevent blindness from diabetic retinopathy, periodic screening and early diagnosis are neccessary. Due to lack of expert ophthalmologists in rural area, automated early exudate (one of visible sign of diabetic retinopathy) detection could help to reduce the number of blindness in diabetic patients. Traditional automatic exudate detection methods are based on specific parameter configuration...

Background: Microarray experiments can simultaneously determine the expression of thousands of genes. Identification of potential genes from microarray data for diagnosis of cancer is important. This study aimed to identify genes for the diagnosis of acute myeloid and lymphoblastic leukemia using a sparse feature selection method. Materials and Methods: In this descriptive study, the expressio...

In this paper, two classifiers are proposed to distinguish between bulking and nonbulking situations in an activated sludge wastewater treatment plant, based on available image analysis information. The first classifier consists of a simple linear classification function, while the second classifier uses a highly nonlinear least squares support vector machine (LS-SVM) to distinguish between bot...