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An RBF-PSO Based Approach for Modeling Prostate Cancer

Research paper by Emma Perracchione, Ilaria Stura

Indexed on: 12 Dec '15Published on: 12 Dec '15Published in: Quantitative Biology - Tissues and Organs



Abstract

Prostate cancer is one of the most common cancers in men. It is characterized by a slow growth and it can be diagnosed in an early stage by observing the Prostate Specific Antigen (PSA). However, a relapse after the primary therapy could arise and different growth characteristics of the new tumor are observed. In order to get a better understanding of the phenomenon, a mathematical model involving several parameters is considered. To estimate the values of the parameters identifying the disease risk level a novel approach, based on combining Particle Swarm Optimization (PSO) with a meshfree interpolation method, is proposed.