Výsledky vyhledávání - "Stefania DESSÌ"

Hypotensive infarction of the spinal cord or acute spinal cord infarction presenting with chest pain?

Autor: Anna L. ALIMONDA, Francesca PITZUS, Stefania DESSÌ, Daniela MURGIA, Francesco ARCA, Fabrizio POLO

Publikováno v: Italian Journal of Emergency Medicine. 11

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2830980f4e63c2328468cd0f821e979d
https://doi.org/10.23736/s2532-1285.22.00120-3

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An Observational Study on the Factors of Successful Aging in a Sample of Nonagenarian Patients in a Rehabilitation Hospital Complex

Autor: Stefania Dessì, Alessandra De Francesco, Paola Vizzuso, Maria Elena Boero

Publikováno v: Journal of Population Ageing. 10:403-416

The number of individuals aged sixty and older is expected to increase from 605 million in 2000 to over two billion in 2050. As a consequence the number of elderly medicare beneficiaries likely to be frail will triple. Our study explored the factors

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9b9d68cbeabb4a9d7c79f650f4963c3e
https://doi.org/10.1007/s12062-017-9175-5

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Exploring the Relatedness of Gene Sets

Autor: Emanuele Pascariello, Barbara Pes, Nicoletta Dessì, Stefania Dessì

Publikováno v: Computational Intelligence Methods for Bioinformatics and Biostatistics ISBN: 9783319244617
CIBB

A key activity for life scientists is the exploration of the relatedness of a set of genes in order to differentiate genes performing coherently related functions from random grouped genes. This paper considers exploring the relatedness within two po

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b610b861d8e39c5d9bbcc7d83c642bfa
https://doi.org/10.1007/978-3-319-24462-4_4

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A Fully Semantic Approach to Large Scale Text Categorization

Autor: Nicoletta Dessì, Barbara Pes, Stefania Dessì

Publikováno v: Information Sciences and Systems 2013 ISBN: 9783319016030
ISCIS

Text categorization is usually performed by supervised algorithms on the large amount of hand-labelled documents which are labor-intensive and often not available. To avoid this drawback, this paper proposes a text categorization approach that is des

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9e926840fcffd9cae599d2f969ebf6aa
https://doi.org/10.1007/978-3-319-01604-7_15

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