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Integration and analysis of heterogeneous big data for precision medicine and suggested treatments for different types of patients

The vision of IASIS was to turn the wave of data heading our way into actionable knowledge for decision makers. This was achieved by integrating data from disparate sources, including genomics, electronic health records and bibliography, and applying advanced analytics methods to discover useful patterns. Big Data in healthcare is in its early days, and most of the potential for value creation is being unclaimed. The integration and analysis of heterogeneous sources of information will enable the best decisions to be made, allowing for diagnosis and treatment to be personalised to each individual. IASIS aimed to pave the way towards comprehensive access to data from disparate sources and the results of analysis, in the form of actionable knowledge for policy-making. The infrastructure was able to convert clinical notes into usable data, combine them with genomic data, related bibliography, image data and more, and create a global knowledge base. This facilitated the use of intelligent methods in order to discover useful patterns across different resources. Using semantic integration of data gave the opportunity to generate information that was rich, auditable and reliable. Data resources for two different disease categories were explored, dementia and lung cancer.

The IASIS Consortium was coordinated by National Center for Scientific Research “Demokritos” (Greece) and consisted of the following partners: Athens Technology Center SA (Greece), University of Bonn (Germany), Universidad Politécnica de Madrid (Spain), Puerta de Hierro Hospital, Madrid (Spain), St George’s Hospital Medical School, University of London (United Kingdom), Alzheimer’s Research UK (United Kingdom), Spanish Lung Cancer Group (Spain), Centre for Genomic Regulation (Spain) and University of Maryland (United States of America).

ATC in the IASIS project was actively involved both in R&D and commercial activities relevant to Big Data analytics. Having commercial products addressing the data needs of media companies but also large enterprises, ATC had a strong interest in advancing the relevant technologies in order to remain competitive in the fast moving sector of Big Data. As a software SME, ATC provides a flexibility in using technologies and has no dependencies with specific tools and framework, forming a natural integration leader. ATC also led the activities related to Exploitation.

The project started in April 2017 and had a duration of 39 months.

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