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Enabling heterogeneous data integration and biomedical event prediction through ICT: The test case of cancer reoccurrence

: Picone, Marco; Steger, Sebastian; Exarchos, Konstantinos; Fazio, Marco De; Goletsis, Yorgos; Fotiadis, Dimitrios I.; Martinelli, Elena; Ardigo, Diego


Arabnia, H.R.:
Software tools and algorithms for biological systems
New York: Springer Science+Business Media, 2011 (Advances in experimental medicine and biology 696)
ISBN: 978-1-4419-7045-9
ISSN: 0065-2598
Book Article
Fraunhofer IGD ()
Medical Informatics; medical image processing; knowledge discovery; data integration; data visualization

Early prediction of cancer reoccurrence constitutes a challenge for oncologists and surgeons. This paper 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 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.