Breast Cancer Risk Assessment
According to the World Health Organization, starting from 2010, cancer will become the leading cause of death worldwide. Prevention of major cancer localizations through a quantified assessment of risk factors is a major concern in order to decrease their impact in our society. In this project our objective was to find and to evaluate modeling methods easily readable by a physician.
This work is based on the thesis work of Gauthier Emilien (PhD defense in 2013).
Laurent Brisson
Associate Professor
Laurent BRISSON received a Ph.D degree in Computer Science from Université Nice Sophia-Antipolis (France) in 2006. His work focuses on the analysis of social networks along two axes: information dissemination and the detection of temporal communities.
Publications
(2015).
A Nearest Neighbor Approach to Build a Readable Risk Score for Breast Cancer.
Real World Data Mining Applications, Annals of Information Systems.
(2012).
Challenges to building a platform for a breast cancer risk score.
RCIS 2012: 6th International Conference on Research Challenges in Information Science, Valencia, Spain.
(2011).
Breast cancer risk score: a data mining approach to improve readability.
The International Conference on Data Mining, Las Vegas, United States.