Nonlinear Projection Methods for Prediction of Trends in Cancer Incidence and Mortality

Main aim of this project is to develop a prediction model for cancer projection, with detailed information regarding incidence, mortality and other measures of cancer burden for the most common types of cancer, presented by age, sex, time and geographic locations. These data can help stimulatenew research as well as assist decision-making and priority-setting at the individual, community, provincial/territorial and national levels. This prediction Model can be implemented by using historical data to model trends of cancer risk, and extrapolating the trends into the future to project the rates and numbers. Monitoring cancer incidence and mortality time trends is essential for cancer research and health-care planning.

Faculty Supervisor:

William Melek

Student:

Partner:

Alpha Global IT

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Waterloo

Program: