Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Antonio, De Nigro"'
Autor:
Dimosthenis Kyriazis, Francesco Torelli, Antonio De Nigro, Argyro Mavrogiorgou, Athanasios Kiourtis, Domenico Martino
Publikováno v:
ICT4AWE
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0bdaceb8c0e1e7ec3729dfebc173fa10
https://doi.org/10.5220/0010509300002931
https://doi.org/10.5220/0010509300002931
Autor:
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
Publikováno v:
Studies in health technology and informatics
r-IIS La Fe. Repositorio Institucional de Producción Científica del Instituto de Investigación Sanitaria La Fe
instname
r-IIS La Fe. Repositorio Institucional de Producción Científica del Instituto de Investigación Sanitaria La Fe
instname
The aim of this paper is to present examples of big data techniques that can be applied on Holistic Health Records (HHR) in the context of the CrowdHEALTH project. Real-time big data analytics can be performed on the stored data (i.e. HHRs) enabling
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::23f23c45eecf2f60ce713a1c7738e97f
https://fundanet.iislafe.san.gva.es/publicaciones/ProdCientif/PublicacionFrw.aspx?id=11151
https://fundanet.iislafe.san.gva.es/publicaciones/ProdCientif/PublicacionFrw.aspx?id=11151
Autor:
R. Scognamiglio, Paolo Zampognaro, Piero Corte, Antonio De Nigro, Maria Luisa Villani, Amedeo Falanga, Gloria Renna, Massimiliano Di Penta, Gerardo Canfora, Raffaele Esposito, Francesco Torelli, Debora Desideri
Publikováno v:
ACM SIGSOFT Software Engineering Notes. 30:1-6
Web services constitute a promising technology to support autonomic computing. Automatic discovery of new services, their composition and binding based on Quality of Service (QoS) are just some of the most promising features that can be provided usin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b70ea01974927a3f87a38c47eba59b3
https://doi.org/10.1145/1082983.1083087
https://doi.org/10.1145/1082983.1083087
Autor:
Gabriele Bavota, Pawel Kedziora, Yacine Rebahi, Francesco Torelli, Ilknur Chulani, Massimiliano Di Penta, Alicja Ciemniewska, Sergio Garcia Villalonga, Roberto Pratola, Ilaria Lener, Juliusz Pukacki, Thomas F. Gordon, Davide Galletti, Antonio De Nigro, Roberto Galoppini
Publikováno v:
CSMR-WCRE
This paper describes the MARKOS (the MARKet for Open Source) European Project, a FP7-ICT-2011-8 STREP project, which aims to realize a service and an interactive application providing an integrated view on the open source projects available on the we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ba50af680681a758b0d1d12e523bf4c
https://doi.org/10.1109/csmr-wcre.2014.6747204
https://doi.org/10.1109/csmr-wcre.2014.6747204
Autor:
Antonio De Nigro, Konstantinos Perakis, Argyro Mavrogiorgou, Andriana Magdalinou, Lydia Montandon, Dimosthenis Kyriazis, Dimitris Miltiadou, Francesco Torelli
Publikováno v:
Acta Informatica Medica
Introduction: With With the proliferation of available ICT services, several sensors and health applications have become ubiquitous, while many applications have been developed to detect certain health conditions and early signs of disease. Currently
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b084efd35333bafcb6c98b2b2f91523
Autor:
Melillo, Fabio, Pandolfo, Claudia
This deliverable presents the first release of the functional and non-function specifications of the iHELP solution, that will guide the development activities throughout the project, in order to achieve a consensus on what the iHelp platform will of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::655e6db7106c45b00d5394d60d97c8a8
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