D. Soudris, S. Xydis, Christos Baloukas, A. Hadzidimitriou, I. Chouvarda, K. Stamatopoulos, N. Maglaveras, John Chang, Andreas Raptopoulos, D. Manset, B. Pierscionek, R. Kayyali, N. Philip, Tobias Becker, K. Vaporidi, Eumorphia Kondili, D. Georgopoulos, L. Sutton, R. Rosenquist, L. Scarfò, P. Ghia
{"title":"AEGLE: A big bio-data analytics framework for integrated health-care services","authors":"D. Soudris, S. Xydis, Christos Baloukas, A. Hadzidimitriou, I. Chouvarda, K. Stamatopoulos, N. Maglaveras, John Chang, Andreas Raptopoulos, D. Manset, B. Pierscionek, R. Kayyali, N. Philip, Tobias Becker, K. Vaporidi, Eumorphia Kondili, D. Georgopoulos, L. Sutton, R. Rosenquist, L. Scarfò, P. Ghia","doi":"10.1109/SAMOS.2015.7363682","DOIUrl":null,"url":null,"abstract":"AEGLE project1 targets to build an innovative ICT solution addressing the whole data value chain for health based on: cloud computing enabling dynamic resource allocation, HPC infrastructures for computational acceleration and advanced visualization techniques. In this paper, we provide an analysis of the addressed Big Data health scenarios and we describe the key enabling technologies, as well as data privacy and regulatory issues to be integrated into AEGLE's ecosystem, enabling advanced health-care analytic services, while also promoting related research activities.","PeriodicalId":346802,"journal":{"name":"2015 International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation (SAMOS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation (SAMOS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAMOS.2015.7363682","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
AEGLE project1 targets to build an innovative ICT solution addressing the whole data value chain for health based on: cloud computing enabling dynamic resource allocation, HPC infrastructures for computational acceleration and advanced visualization techniques. In this paper, we provide an analysis of the addressed Big Data health scenarios and we describe the key enabling technologies, as well as data privacy and regulatory issues to be integrated into AEGLE's ecosystem, enabling advanced health-care analytic services, while also promoting related research activities.