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  5. Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά)
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Please use this identifier to cite or link to this item: https://olympias.lib.uoi.gr/jspui/handle/123456789/13909
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dc.contributor.authorPicone, M.en
dc.contributor.authorSteger, S.en
dc.contributor.authorExarchos, K.en
dc.contributor.authorDe Fazio, M.en
dc.contributor.authorGoletsis, Y.en
dc.contributor.authorFotiadis, D. I.en
dc.contributor.authorMartinelli, E.en
dc.contributor.authorArdigo, D.en
dc.date.accessioned2015-11-24T17:33:54Z-
dc.date.available2015-11-24T17:33:54Z-
dc.identifier.issn0065-2598-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/13909-
dc.rightsDefault Licence-
dc.subjectcancer informaticsen
dc.subjectexperimental medicine and analysis toolsen
dc.subjectimage processing in medicine and biological sciencesen
dc.subjectbiological data mining and knowledge discoveryen
dc.subjectbiological data integration and visualizationen
dc.subjectlymph-nodesen
dc.subjectsegmentationen
dc.titleEnabling Heterogeneous Data Integration and Biomedical Event Prediction Through ICT: The Test Case of Cancer Reoccurrenceen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primaryDoi 10.1007/978-1-4419-7046-6_37-
heal.identifier.secondary<Go to ISI>://000289694000037-
heal.identifier.secondaryhttp://www.springerlink.com/content/k84uq16873736030/fulltext.pdf-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Επιστήμης Υλικώνel
heal.publicationDate2011-
heal.abstractEarly prediction of cancer reoccurrence constitutes a challenge for oncologists and surgeons. This chapter describes one ongoing experience, the EU-Project NeoMark, where scientists from different medical and biology research fields joined efforts with Information Technology experts to identify methods and algorithms that are able to early predict the reoccurrence risk for one of the most devastating tumors, the oral cavity squamous cell carcinoma (OSCC). The challenge of NeoMark is to develop algorithms able to identify a "signature" or bio-profile of the disease, by integrating multiscale and multivariate data from medical images, genomic profile from tissue and circulating cells RNA, and other medical parameters collected! from patients before and after treatment. A limited number of relevant biomarkers will be identified and used in a real-time PCR device for early detection of disease reoccurrence.en
heal.publisherSpringer-Verlagen
heal.journalNameSoftware Tools and Algorithms for Biological Systemsen
heal.journalTypepeer reviewed-
heal.fullTextAvailabilityTRUE-
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