VATE: VAlidation of high TEchnology based on large database analysis by learning machine. (October 2014)

• Record Type: Journal Article
• Authors: Meldolesi, Elisa; van Soest, Joahn; Alitto, Anna Rita; Autorino, Rosa; Dinapoli, Nicola; Dekker, Andre; Gambacorta, Maria Antonietta; Gatta, Roberto; Tagliaferri, Luca; Damiani, Andrea; Valentini, Vincenzo
• Is Part Of: Colorectal cancer. Volume 3:Number 5(2014)
• Page Start: 435
• Page End: 450
• Publication Date: 2014-10
• Subjects: data mining -- high technology -- individualized medicine -- large database -- ontology -- predictive model -- Semantic Web; Colon (Anatomy) -- Cancer -- Periodicals; Rectum -- Cancer -- Periodicals; 616.994347
• DOI: 10.2217/crc.14.34
• Languages: English
• ISSNs: 1758-194X

Abstract

SUMMARY : The interaction between implementation of new technologies and different outcomes can allow a broad range of researches to be expanded. The purpose of this paper is to introduce the VAlidation of high TEchnology based on large database analysis by learning machine (VATE) project that aims to combine new technologies with outcomes related to rectal cancer in terms of tumor control and normal tissue sparing. Using automated computer bots and the knowledge for screening data it is possible to identify the factors that can mostly influence those outcomes. Population-based observational studies resulting from the linkage of different datasets will be conducted in order to develop predictive models that allow physicians to share decision with patients into a wider concept of tailored treatment.