Big data, Page Ranking and medical application
Big data, Page Ranking and Application
By Pr. Nahid Emad, Maison de la Simulation / PRiSM , Université de Versailles
The surge of medical and nutritional data in the field of health requires research of models and methods as well as the development of data analysis tools. The spread of infectious diseases, detection of biomarkers for prognosis and diagnosis of the disease, research of indicators for personalized nutrition and/or medical treatment, are some typical examples of problems to solve. In this talk, we focus on the spread of contagious diseases and show how the eigenvalue equation intervenes in models of infectious disease propagation and could be used as an ally of vaccination campaigns in the actions carried out by health care organizations. The stochastic model based on PageRank allows simulating the epidemic spread, where a PageRank-like infection vector is calculated to help establish efficient vaccination strategy. Due to the size and the particular structure of underlying social networks, this calculation requires considerable computational resources as well as storage means of very large quantity of data and represents a big challenge in high performance computing. The computation methods of PageRank in this context are explored. The experiments take into account very large network of individuals imposing the challenging issue of handling very big graph with complex structure. The computational challenges of some other applications such as identification of biomarkers for prognosis and diagnosis of a disease will also be discussed.
Nahid Emad received the Habitation to Direct Researches (HDR) in Computer Science from University of Versailles in 2001, the Ph.D. and MS in Applied Mathematics from Pierre et Marie Currie University (Paris VI) in 1989 and 1983. She is Professor and leads the Intensive Numerical Computation group of Computer Science department at the University of Versailles. She is the advisor of 14 Ph.D. and authored more than 140 papers in international journals and conferences. She is specialized in numerical algorithms in linear algebra, parallel and distributed computing and software engineering for parallel and distributed numerical computing.