Turgay Ayer, Oguzhan Alagoz, Jagpreet Chhatwal, Jude W. Shavlik, Charles E. Kahn Jr and Elizabeth S. Burnside Breast cancer risk estimation with artificial neural networks revisited Cancer 116
Article first published online: 27 APR 2010 | DOI: 10.1002/cncr.25081
In the past, several artificial neural network (ANN) models have been developed for breast cancer-risk prediction based on discrimination performance, but none have assessed calibration, which is an equally important measure of accurate risk prediction. In this study, we show that an ANN trained on a large dataset of consecutive mammography findings can successfully discriminate malignant abnormalities from benign ones and accurately predict the probability of breast cancer for individual patients.
Complete the form below and we will send an e-mail message containing a link to the selected article on your behalf
Required = Required Field