Prediction of breast cancer biopsy outcomes using a distributed genetic programming approach

Simone A. Ludwig
2010 Proceedings of the ACM international conference on Health informatics - IHI '10  
Worldwide, breast cancer is the second most common type of cancer after lung cancer and the fifth most common cause of cancer death. In 2004, breast cancer caused 519,000 deaths worldwide. In order to reduce the cancer deaths and thereby to increase the survival rates an automatic approach is necessary to aid physicians in the prognosis of breast cancer. The most effective method for breast cancer screening today is mammography. However, the predictions of the breast biopsy resulting from
more » ... ram interpretation leads to approximately 70 % biopsies with benign outcomes, which could have been prevented. Therefore, an automatic method is necessary to aid physicians in the prognosis of mammography interpretations. The data set used is based on BI-RADS findings. Previous work has achieved good results using a decision tree, an artificial neural networks and a case-based reasoning approach to develop predictive classifiers. This paper uses a distributed genetic programming approach to predict the outcomes of the mammography achieving even better prediction results.
doi:10.1145/1882992.1883099 dblp:conf/ihi/Ludwig10 fatcat:kdtufkzsfrhtjoralgbzgscfzq