In order to investigate the breast cancer prediction problem on the aging population with the grades of DCIS, we conduct a tree augmented naive Bayesian network experiment trained and tested on a large clinical dataset including consecutive diagnostic mammography examinations, consequent biopsy outcomes and related cancer registry records in the population of women across all ages. The aggregated results of our ten-fold cross validation method recommend a biopsy threshold higher than 2% for the aging population.
@article{arxiv.1506.05776,
title = {A tree augmented naive Bayesian network experiment for breast cancer prediction},
author = {Ping Ren},
journal= {arXiv preprint arXiv:1506.05776},
year = {2015}
}