George Paliouras is a research director and head of the Intelligent Information Systems division of the Institute of Informatics and Telecommunications at NCSR "Demokritos", Greece. He holds a PhD in Machine Learning and has performed basic and applied research in Artificial Intelligence for the last 25 years. He is interested in the development of novel methods for addressing challenging big and small data analysis problems, such as learning complex models from structured relational data, learning from noisy and sparse data, learning from multiple heterogeneous data streams, discovering patterns in hypergraphs. He is motivated by research that addresses real-world problems and has contributed in a variety of such problems, ranging from spam filtering and Web personalization to biomedical information retrieval. He has co-founded the spin-off company i-sieve technologies that provides online reputation monitoring services.
Among various contributions to the research community, he has served as board member in national and international scientific societies; he is serving in the editorial board of international journals and has chaired international conferences. He is involved in several research projects and has the role of scientific coordinator/principal investigator in some of them. In particular, he has coordinated the BioASQ project, that was funded by the European Commission and provided the infrastructure for the BioASQ challenge on biomedical semantic indexing and Question Answering. He is currently coordinating the project iASiS, also funded by the European Commission to develop big data integration and analysis methods that will provide insight to public health policy-making for personalized medicine.
There are three main reasons for an immediate innovation action to apply big data technologies in Healthcare. Firstly, a Healthy nation is a Wealthy nation! An improvement in health leads to economic growth through long-term gains in human and physical capital, which ultimately raises productivity and per capita GDP. Secondly, Healthcare is one of the most expensive sectors, which accounts for 10% of the EU’s GDP continuously becoming more expensive. Thirdly, as healthcare is traditionally very conservative with adopting ICT, while big healthcare data is becoming available, the expected impact of applying big data technologies in Healthcare is enormous. BigMedilytics will transform Europe’s Healthcare sector by using state-of-the-art Big Data technologies to achieve breakthrough productivity in the sector by reducing cost, improving patient outcomes and delivering better access to healthcare facilities simultaneously, covering the entire Healthcare Continuum – from Prevention to Diagnosis, Treatment and Home Care throughout Europe.
• A Big Data Healthcare Analytics Blueprint (defining platforms and components), which enables data integration and innovation spanning all the key players across the Healthcare Data Value Chains
• Instantiations of the Blueprint which implement BigMedilytics concepts across 12 large-scale pilots accounting for an estimated 86% of deaths and 77% of the disease burden in Europe
• The Best “Big Data technology and Healthcare policy” Practices related to big data technologies, new business models and European and national healthcare data policies and regulations.
BigMedilytics will maximize the impact by using its Big Data Healthcare Analytics Blueprint and the Best Practices to scale-up the concepts demonstrated in the 12 pilots, to the whole Healthcare sector in Europe. It will use health records of more than 11 million patients across 8 countries and data from other sectors such as insurance and public sector.