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pro vyhledávání: '"Jacob Roldan"'
The iHelp integrated solution aims at providing personalised health monitoring and decision support based on artificial intelligence using datasets coming from a variety of different and heterogeneous sources that will be integrated into a common dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25e6813b0643356dec253a5794af69c9
Autor:
Maria Angeles Sanguino Gonzalez, Jorge Montero Gomez, Tomas Pariente Gomez, Ricard Munnè, Giuseppe La Rocca, Ofer Biran, Yosef Moatti, Oshrit Feder, Chris Maragkos, Kostas Moutselos, Vrettos Moulos, Panayiotis Tsanakas, Panayiotis Michael, A. Bettiol, M. Taborda Barata, Rafael Del Hoyo, Ben Williams, Sarah Frost, Adil Mohammed Ali, Jose Maria Zaragoza, Jacob Roldan, Patricio Martinez, Javier Lopez Moratalla, Sadra Ebro, Armend Duzha, Nikos Achilleopoulos, Petya Bozhkova, Konstantinos Nasias, Javier Sancho, Iskra Yovkova, Konstantinos Oikonomou, Giannis Ledakis, Thanos Kiourtis, Ilias Maglogiannis, Argyro Mavrogiorgou, George Manias, Nikitas Marinos Sgouros, Dimosthenis Kyriazis
This document provides the first update to the Conceptual Model and Reference Architecture of PolicyCLOUD (the initial document has been submitted as Deliverable D2.2). This second version (Deliverable D2.6) provides the definition of the overall arc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::09d21ade05cd6f4023f8f48885781b5b
Autor:
Yosef Moatti, Paula Ta Shma, Guy Khazma, Javier López Moratalla, Jacob Roldan, Rogelio Rodriguez, Luis Tomás Bolívar, Marta Patiño, Ainhoa Azqueta, George Makridis, Christos Doulkeridis, Maria Kanakari, Dimitris Poulopoulos, Giannis Poulakis, Nikitas Sgouros, Richard Mccreadie
The BigDataStack project was conceived as a data centric environment, integrating approaches for Data as a Service (DaaS). The data services of this environment are naturally at the core of BigDataStack and are covered in this deliverable in terms of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e4553adbd478dc0fb4652b12335378c
Autor:
Fabio Melillo
iHelp aims to early detect and mitigate the risks associated with Pancreatic Cancer applying advanced Artificial Intelligence (AI)-based techniques to support the actors of the system. Those techniques are performed on historic data of cancer patient
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0bb96e6918753109de63bf8357a89881