Mathematical Analysis and Computational Integration of Massive Heterogeneous Data from the Human Retina

Abstract : Modern epidemiology integrates knowledge from heterogeneous collections of data consisting of numerical, descriptive and imaging. Large-scale epidemiological studies use sophisticated statistical analysis, mathematical models using differential equations and versatile analytic tools that handle numerical data. In contrast, knowledge extraction from images and descriptive information in the form of text and diagrams remain a challenge for most fields, in particular, for diseases of the eye. In this article we provide a roadmap towards extraction of knowledge from text and images with focus on forthcoming applications to epidemiological investigation of retinal diseases, especially from existing massive heterogeneous collections of data distributed around the globe.
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Luis M. Camarinha-Matos; Ehsan Shahamatnia; Gonçalo Nunes. 3rd Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Feb 2012, Costa de Caparica, Portugal. Springer, IFIP Advances in Information and Communication Technology, AICT-372, pp.571-578, 2012, Technological Innovation for Value Creation. 〈10.1007/978-3-642-28255-3_63〉
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Arash Sangari, Adel Ardalan, Larry Lambe, Hamid Eghbalnia, Amir Assadi. Mathematical Analysis and Computational Integration of Massive Heterogeneous Data from the Human Retina. Luis M. Camarinha-Matos; Ehsan Shahamatnia; Gonçalo Nunes. 3rd Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Feb 2012, Costa de Caparica, Portugal. Springer, IFIP Advances in Information and Communication Technology, AICT-372, pp.571-578, 2012, Technological Innovation for Value Creation. 〈10.1007/978-3-642-28255-3_63〉. 〈hal-01365778〉

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