Application of time series analysis to model and understand Cancer indices

• Grant number: 14/03352-8
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: May 01, 2014
• End date: March 31, 2015
• Field of knowledge: Physical Sciences and Mathematics - Computer Science
• Principal Investigator: Rodrigo Fernandes de Mello
• Grantee: Anderson Caio Santos Silva
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Associated scholarship(s): 14/20430-2 - Employing small-shuffle surrogate technique to understand the deterministic levels of cancer data, BE.EP.IC

Abstract

Several systems and phenomena produce outputs over time. Many of those phenomena, specially the ones related to health, require additional attention of the society. Among those phenomena, it is important to understand the conditions certain types of cancer develop and their relations with other factors or variables. In this context, this project will apply Time Series Analysis tools to model and understand the relations among the occurrence of types of cancer around the World and particular aspects of patients. This work will consider the datasets made available by the International Association of Cancer Registries. As contribution, we intend to understand if data comes from a deterministic or a stochastic source and how they are related to other variables such as ethnic group, gender, age, etc.