Nonlinear Recognition Methods for Oncological Pathologies

Gregorio Patrizi (), Vincenzo Pietropaolo (), Antonella Carbone (), Renato Leone (), Laura Giacomo (), Valentina Losacco () and Giacomo Patrizi ()
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Gregorio Patrizi: “Sapienza”-University of Rome
Vincenzo Pietropaolo: “Sapienza”-University of Rome
Antonella Carbone: “Sapienza”-University of Rome
Renato Leone: Universitá di Camerino
Laura Giacomo: Probabilita e Statistiche Applicate
Valentina Losacco: Probabilita e Statistiche Applicate
Giacomo Patrizi: Probabilita e Statistiche Applicate

Chapter Chapter 9 in Data Mining for Biomarker Discovery, 2012, pp 169-185 from Springer

Abstract: Abstract A biomarker, or biological marker is a substance used as an indicator of a biological state. It is used in many scientific fields. The determination and function of the biomarker can be formalized more precisely by using Nonlinear Recognition Methods for accurate identification of oncological pathologies and both the pathogenic processes and pharmacologic response to a therapeutic intervention by applying dynamical systems and chaotic algorithms to determine the biological state and its dynamics. To this end a classification problem is solved based on optimal nonlinear algorithm, and it will be shown that certainty equivalent predictions are derived. Application results will be given on available test data sets of gastroscopic and colonoscopic images. The increase in the recognition accuracy is attributable to the algorithm and a strict statistical methodology without extraneous assumptions.

Keywords: Variational Inequality; Trust Region; Membership Class; Identical Pattern; Nonlinear Complementarity Problem (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/978-1-4614-2107-8_9

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