Title :
Breast cancer prediction using a neural network model
Author :
Nastac, l. ; Jalava, P. ; Collan, Mikael ; Collan, Y. ; Kuopio, T. ; Back, Barbro
Author_Institution :
TUCS, Abo Akademi University, Finland
fDate :
June 28 2004-July 1 2004
Abstract :
This paper reports results on using an artificial neural network (ANN) for predicting the estrogen receptor (ER) status, which is not always available, but has a place in therapy selection of breast cancer. Our results show that in more than two thirds of the cases, the ANN is able to predict the correct ER status. An optimum neural architecture was rescarched, and optimal outpoint for prediction selected on the basis of clinical data.
Keywords :
Artificial neural networks; Back; Breast cancer; Erbium; Hospitals; Laboratories; Neoplasms; Neural networks; Pathology; Predictive models; ER; efficiency; neural network; outpoint; prediction; sensitivity; specificity; test; training;
Conference_Titel :
Automation Congress, 2004. Proceedings. World
Conference_Location :
Seville
Print_ISBN :
1-889335-21-5