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Pandemic influenza has great potential to cause large and rapid increases in deaths and serious illness. The objective of this paper is to develop an agent-based model to simulate the spread of pandemic influenza (novel H1N1) in Egypt. The proposed multi-agent model is based on the modeling of individuals' interactions in a space-time context. The proposed(More)
DBSCAN is a pioneer density based clustering algorithm. It can find out the clusters of different shapes and sizes from the large amount of data which is containing noise and outliers. But the clusters detected by it contain large amount of density variation within them. It can not handle the local density variation that exists within the cluster. For good(More)
In this paper, a new hybrid adaptation model for cancer diagnosis has been developed. It combines transformational and hierarchical adaptation techniques with artificial neural networks (ANN's) and certainty factors (CF's). The model consists of a hierarchy of three phases, which simulates the expert doctor phases of cancer diagnosis. Each phase uses a(More)
Keywords: Human brain tumors Medical imaging Medical informatics Magnetic resonance images Segmentation Feature extractions Classification Intelligent computer-aided diagnosis systems a b s t r a c t Computer-aided detection/diagnosis (CAD) systems can enhance the diagnostic capabilities of physicians and reduce the time required for accurate diagnosis. The(More)
PARKINSON'S DISEASE IS A NEURODEGENERATIVE DISORDER WITH A LONG TIME COURSE AND A SIGNIFICANT PREVALENCE, WHICH INCREASES SIGNIFICANTLY WITH AGE. ALTHOUGH THE ETIOLOGY IS CURRENTLY UNKNOWN, THE DISEASE PRESENTS WITH NEURODEGENERATION OF REGIONS OF THE BASAL GANGLIA. THE ONSET OCCURS LATER IN LIFE, AND THE DISEASE PROGRESSES SLOWLY. THE DISEASE IS DIAGNOSED(More)
– Self-Organizing Feature map (SOFM) is a competitive neural network in which neurons are organized in an l-dimensional lattice (grid) representing the feature space. The principal goal of the SOFM is to transform an incoming pattern of arbitrary dimension into a one-or two-dimensional discrete map, and to perform this transformation adaptively in a(More)
Shape-of-object representation has always been an important topic in image processing and pattern recognition. This work deals with representation of shape based on a new boundary chain code, and uses this chain code to recognize the object. Chain code techniques are widely used to represent an object because they preserve information and allow considerable(More)
Although the electrocardiogram (ECG) has been a reliable diagnostic tool for decades, its deployment in the context of biometrics is relatively recent. Its robustness to falsification, the evidence it carries about aliveness and its rich feature space has rendered the deployment of ECG based biometrics an interesting prospect. The rich feature space(More)