Enabling Heterogeneous Data Integration and Biomedical Event Prediction Through ICT: The Test Case of Cancer Reoccurrence
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Authors
Picone, M.
Steger, S.
Exarchos, K.
De Fazio, M.
Goletsis, Y.
Fotiadis, D. I.
Martinelli, E.
Ardigo, D.
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Springer-Verlag
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peer reviewed
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Software Tools and Algorithms for Biological Systems
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Early 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.
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cancer informatics, experimental medicine and analysis tools, image processing in medicine and biological sciences, biological data mining and knowledge discovery, biological data integration and visualization, lymph-nodes, segmentation
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<Go to ISI>://000289694000037
http://www.springerlink.com/content/k84uq16873736030/fulltext.pdf
http://www.springerlink.com/content/k84uq16873736030/fulltext.pdf
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en
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Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Επιστήμης Υλικών