Year: 2016
Type: conference-paper
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.
Source: AIP conference proceedings
DOI: 10.1063/1.4952182
Authors: Emma Perracchione, Ilaria Stura
Institution: University of Turin
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2263046285