Short bio: dr. Oana GEMAN is Associate Professor Habilitate in Electronics, Telecommunication and Information Technologies at Stefan cel Mare University form Suceava, Romania. She is Medical Bioengineer, with Ph.D. in Electronics and Telecommunication, and a post-doctoral researcher in Computer Science. She has published six books, and six book chapters, has published over 50 ISI articles with an IF over 20. She has been a director or a member in 10 national and international grants.

Her current research interests include: non-invasive measurements of biomedical signals, wireless sensors, signal processing, and processing information by way of Artificial Intelligence such as nonlinear dynamics analysis, stochastic networks and neuro-fuzzy methods, classification and prediction, Data-Mining, Deep Learning, Intelligent Systems, Bioinformatics and Biostatistics and Biomedical Applications. The current project will involve research, dissemination and transfer of knowledge in the area of bioengineering and medical engineering, contributions to the development of system requirements, software development, testing the new system under laboratory conditions, as well as conducting reality simulations.

Title : Big Data Analysis and Applications in Biomedical Field

Abstract : The Human Microbiome is a fundamental component of human physiology, with an estimated one-third of circulating metabolites being a product of the gut microbiota. Changes in the microbiome can trigger changes in human cellular activities, resulting in disease or contribute to its progression. Microbiota is considered to be a virtual “code” or a system emerging, with the properties that must be integrated into the biology and physiology of the human. Unlike the other components, the functions of this “code” are not yet fully understood but can be quite easily disturbed by diet, diseases, and the various treatments. An important step represents the discovery of potential methods of use of human microbiota in prevention and treatment of diseases such as autism, asthma, Parkinson disease, obesity, and diabetes. There is an impressive collection of data (Human Microbiome Big Date) which can be analyzed and classified using the algorithms of Data Mining or Knowledge Discovery Date Tools.

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