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DC Field | Value | Language |
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dc.contributor.author | Exarchos, T.P., | en |
dc.contributor.author | Giannakeas, N., | en |
dc.contributor.author | Goletsis, Y., | en |
dc.contributor.author | Papaloukas, C., | en |
dc.contributor.author | Fotiadis, D.I. | en |
dc.date.accessioned | 2015-11-24T17:05:45Z | - |
dc.date.available | 2015-11-24T17:05:45Z | - |
dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/11374 | - |
dc.rights | Default Licence | - |
dc.subject | Cancer, decision support systems, pattern analysis, profiles, data integration | en |
dc.title | Pattern alalysis and decision support for cancer through clinico-Genomic profiles | en |
heal.type | journalArticle | - |
heal.type.en | Journal article | en |
heal.type.el | Άρθρο Περιοδικού | el |
heal.language | en | - |
heal.access | campus | - |
heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Οικονομικών και Κοινωνικών Επιστημών. Τμήμα Οικονομικών Επιστημών | el |
heal.abstract | Advances in genome technology are playing a growing role in medicine and healthcare. With the development of new technologies and opportunities for large-scale analysis of the genome, genomic data have a clear impact on medicine. Cancer prognostics and therapeutics are among the first major test cases for genomic medicine, given that all types of cancer are related with genomic instability. In this paper we present a novel system for pattern analysis and decision support in cancer. The system integrates clinical data from electronic health records and genomic data. Pattern analysis and data mining methods are applied to these integrated data and the discovered knowledge is used for cancer decision support. Through this integration, conclusions can be drawn for early diagnosis, staging and cancer treatment. | en |
heal.journalType | peer reviewed | - |
heal.fullTextAvailability | TRUE | - |
Appears in Collections: | Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά) - ΟΕ |
Files in This Item:
File | Description | Size | Format | |
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goletsis-pattern alalysis and.pdf | 1.07 MB | Adobe PDF | View/Open Request a copy |
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