Abdel-Badeeh M. Salem

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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)
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)
– 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)
– Cluster analysis is a primary method for data mining. Finding clusters with varying sizes, shapes and densities is a challenging job. DBSCAN can find clusters with varying shapes and sizes. But it has a trouble in finding clusters with varying densities, because it depends on a global value for its parameter Eps. This paper presents enhanced DBSCAN which(More)