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The aim of this work is to present an automated method that assists in the diagnosis of Alzheimer's disease and also supports the monitoring of the progression of the disease. The method is based on features extracted from the data acquired during an fMRI experiment. It consists of six stages: (a) preprocessing of fMRI data, (b) modeling of fMRI voxel time(More)
The heart rate signal contains valuable information about cardiac health, which cannot be extracted without the use of appropriate computerized methods. This paper presents an analysis of various electrocardiograms, the aim of which is to categorize them into two distinct groups. Group A represents young male subjects with no prior occurrence of coronary(More)
In this study, heartbeat time series are classified using support vector machines (SVMs). Statistical methods and signal analysis techniques are used to extract features from the signals. The SVM classifier is favorably compared to other neural network-based classification approaches by performing leave-one-out cross validation. The performance of the SVM(More)
The approximate entropy (ApEn) is a measure of systems complexity. The implementation of the method is computationally expensive and requires execution time analogous to the square of the size of the input signal. We propose here a fast algorithm which speeds up the computation of approximate entropy by detecting early some vectors that are not similar and(More)
Land-cover mapping efforts within the USGS Gap Analysis Program have traditionally been state-centered; each state having the responsibility of implementing a project design for the geographic area within their state boundaries. The Southwest Regional Gap Analysis Project (SWReGAP) was the first formal GAP project designed at a regional, multi-state scale.(More)
The goal of this paper is to examine the classification capabilities of various prediction and approximation methods and suggest which are most likely to be suitable for the clinical setting. Various prediction and approximation methods are applied in order to detect and extract those which provide the better differentiation between control and patient(More)
The decrease in heartbeat variation is an indication of abnormal heart function. Without the help of appropriate computerized methods, physicians are not able to make a diagnosis based on this assumption. Described here is an automated system, ready for clinical use, which will aid in making an accurate diagnosis. It is made up of two sections; an(More)