Ahmet Sertbas

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There has been an increased interest in speech pattern analysis applications of Parkinsonism for building predictive telediagnosis and telemonitoring models. For this purpose, we have collected a wide variety of voice samples, including sustained vowels, words, and sentences compiled from a set of speaking exercises for people with Parkinson's disease.(More)
In this study, we present an evaluation of using various methods for face recognition. As feature extracting techniques we benefit from wavelet decomposition and Eigenfaces method which is based on Principal Component Analysis (PCA). After generating feature vectors, distance classifier and Support Vector Machines (SVMs) are used for classification step. We(More)
MOTIVATION Gene therapy aims at using viral vectors for attaching helpful genetic code to target genes. Therefore, it is of great importance to develop methods that can discover significant patterns around viral integration sites. Canonical correlation analysis is an unsupervised statistical tool that is used to describe the relations between two related(More)
The purpose of this study is to implement accurate methods of detection and classification of benign and malignant breast masses in mammograms. Our new proposed method, which can be used as a diagnostic tool, is denoted Local Seed Region Growing-Spherical Wavelet Transform (LSRG-SWT), and consists of four steps. The first step is homomorphic filtering for(More)
Breast cancer continues to be a significant public health problem in the world. The diagnosing mammography method is the most effective technology for early detection of the breast cancer. However, in some cases, it is difficult for radiologists to detect the typical diagnostic signs, such as masses and microcalcifications on the mammograms. This paper(More)
Parkinson's Disease (PD) is a neurodegenerative motor system disorder, which also causes vocal impairments for most of its patients. A number of recent exploratory studies have evaluated the feasibility of detecting voice disorders by applying data mining tools to acoustic features extracted from speech recordings of patients. Selection of a minimal yet(More)