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Disease surveillance has evolved dramatically in the last few years, becoming more real-time, comprehensive and technology driven. As the Internet grows and evolves as a powerful information medium, the ability to mine real-time news feeds for disease surveillance has become viable. We propose a system, GODSN that monitors global news for disease outbreaks and surveillance. The system processes real-time news feeds using natural language processing to obtain disease information and the geographical reference to plot them on a geographic information system. GODSN provides an effective approach to visualize the spatial and temporal trends of infectious disease outbreaks or disease specific developments.
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