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DC Field | Value | Language |
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dc.contributor.author | Exarchos, K.P., | en |
dc.contributor.author | Goletsis, Y., | en |
dc.contributor.author | Fotiadis, D.I. | en |
dc.date.accessioned | 2015-11-24T17:05:17Z | - |
dc.date.available | 2015-11-24T17:05:17Z | - |
dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/11295 | - |
dc.rights | Default Licence | - |
dc.subject | Multiscale Modeling, Classification, Dynamic Bayesian Networks, Gene Expression, Oral Cancer | en |
dc.title | A multiscale and multiparametric approach for modelling the progression of oral cancer | 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 | In this work we propose a multilevel modeling approach, integrating a multitude of heterogeneous data, in order to model the growth and progression of oral squamous cell carcinoma after remission. Specifically, we employ clinical, imaging and tissue genomic data from the baseline state aiming at the discrimination of patients in high and low risk groups in terms of relapse. Moreover, we collect and analyze gene expression data from circulating blood cells throughout the follow-up period, towards modeling the temporal dimension of the disease. Hence, we capture the underlying mechanism dictating the disease evolvement and employ it for monitoring the status and prognosis of the patients after remission. | 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-a multiscale and.pdf | 407.07 kB | Adobe PDF | View/Open Request a copy |
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