Mathematical Analysis and Computational Integration of Massive   Heterogeneous Data from the Human Retina
  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. 
Arash Sangari, Adel Ardalan, Larry Lambe, Hamid Eghbalnia and Amir H.   Assadi
q-bio.QM cs.IR math.SP