CrowdHEALTH: Big Data Analytics and Holistic Health Records

Parisis Gallos, Santiago Aso, Serge Autexier, Arturo Brotons, Antonio De Nigro, Gregor Jurak, Athanasios Kiourtis, Pavlos Kranas, Dimosthenis Kyriazis, Mitja Lustrek, Andrianna Magdalinou, Ilias Maglogiannis, John Mantas, Antonio Martinez, Andreas Menychtas, Lydia Montandon, Florin Picioroaga, Manuel Perez, Dalibor Stanimirovic, Gregor Starc, Tanja Tomson, Ruth Vilar-Mateo, Ana-Maria Vizitiu

In: Amnon Shabo Shvo, Inge Madsen, Hans-Ulrich Prokosch, Kristiina Häyrinen, Klaus-Hendrik Wolf, Fernando Martín-Sánchez, Matthias Löbe, Thomas M. Deserno (editor). ICT for Health Science Research - Proceedings of the EFMI 2019 Special Topic Conference - 7-10 April 2019, Hanover, Germany. EFMI Special Topic Conference (EFMI STC-2019) April 7-10 Hanover Germany Pages 255-256 Studies in Health Technology and Informatics 258 ISBN 978-1-61499-958-4 IOS Press 4/2019.


The current paper aims to present how real-time big data analytics can be applied on Holistic Health Records (HHR) in the context of the CrowdHEALTH project. CrowdHEALTH platform includes several components, fulfilling different layers regarding data manipulation, health analytics, and health policies. In the context of data manipulation components such as the “Data Converter”, the “Data Cleaner”, the “Data Aggregator”, or the “Data Anonymizer” have been implemented, each one serving different data processing purposes, including state-of-the art technologies.


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German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz