Intelligent patient profiling for diagnosis, staging and treatment selection in colon cancer

dc.contributor.authorGoletsis, Y.,en
dc.contributor.authorExarchos, T.P.,en
dc.contributor.authorGiannakeas, N.,en
dc.contributor.authorFotiadis, D.I.en
dc.date.accessioned2015-11-24T17:04:25Z
dc.date.available2015-11-24T17:04:25Z
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/11175
dc.rightsDefault Licence-
dc.titleIntelligent patient profiling for diagnosis, staging and treatment selection in colon canceren
heal.abstractThe selection of a personalized treatment plan for a patient with cancer can be of critical importance for his health or even survival. A Decision Support Platform that can associate the patient clinical situation with the patient DNA Single Nucleotide Polymorphisms (SNPs) can provide the oncologist with a better understanding of the personalized conditions of every single patient. In this paper we present the MATCH plarform which performs data integration between medicine and molecular biology, by developing a framework where, clinical and genomic features are appropriately combined in order to handle colon cancer diseases. The core of the platform is based on clustering techniques which provide profiles of patients with similar clinical features and genetic predispositions to cancer. The patients which share the same profile should probably have similar treatment plan and follow up. Through the integration of the clinical and genetic data of a patient, real time conclusions can be drawn for his early diagnosis, staging and more effective colon cancer treatment. Intelligent components are designed and developed which identify single nucleotide polymorphisms (SNPs) from the gene sequences and combine them with the clinical situation of the patient. The produced clinico-genomic profiles are used as a decision support tool for newly sequenced patients.en
heal.accesscampus-
heal.fullTextAvailabilityTRUE-
heal.journalTypepeer reviewed-
heal.languageen-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Οικονομικών και Κοινωνικών Επιστημών. Τμήμα Οικονομικών Επιστημώνel
heal.typejournalArticle-
heal.type.elΆρθρο Περιοδικούel
heal.type.enJournal articleen

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