VATE: VAlidation of high TEchnology based on large database analysis by learning machine | Zendy

Elisa Meldolesi | Zendy; Johan van Soest | Zendy; A.R. Alitto | Zendy; Rosa Autorino | Zendy; N. Dinapoli | Zendy; André Dekker | Zendy; Maria Antonietta Gambacorta | Zendy; Roberto Gatta | Zendy; Luca Tagliaferri | Zendy; Andrea Damiani | Zendy; Vincenzo Valentini | Zendy

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VATE: VAlidation of high TEchnology based on large database analysis by learning machine

Author(s) -

Elisa Meldolesi,

Johan van Soest,

A.R. Alitto,

Rosa Autorino,

N. Dinapoli,

André Dekker,

Maria Antonietta Gambacorta,

Roberto Gatta,

Luca Tagliaferri,

Andrea Damiani,

Vincenzo Valentini

Publication year - 2014

Publication title -

colorectal cancer

Language(s) - English

Resource type - Journals

eISSN - 1758-1958

pISSN - 1758-194X

DOI - 10.2217/crc.14.34

Subject(s) - linkage (software) , observational study , machine learning , computer science , medicine , population , artificial intelligence , data science , pathology , biochemistry , chemistry , environmental health , gene

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

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