Title :
Classification the axillary lymph node status of breast cancer patients with the analysis of pattern recognition
Author :
Rukiye Karakış;Mesut Tez;İnan Güler
Author_Institution :
Teknik Eğ
fDate :
4/1/2011 12:00:00 AM
Abstract :
Today one of the prevalent cancer types we come across in women is breast cancer. The determining whether cancer spread axillary lymph nodes or not is very important in staging and determining treatment of breast cancer disease. In this study, clinic and pathologic data of 270 breast cancer patients applied to Ankara Numune Educational and Research Hospital, Ankara Oncology Educational and Research Hospital were used and classified with pattern recognition analysis methods such as multi layer perceptron(MLP), support vector machines(SVM), linear discriminant analysis(LDA), k-nearest neighbour classifier(k-NN). The MLP classifier was obtained the correlation coefficient and the accuracy value of testing dataset as 0.872 and 94.4% respectively.
Keywords :
"Breast cancer","Artificial neural networks","Kernel","Conferences","Signal processing","Lymph nodes"
Conference_Titel :
Signal Processing and Communications Applications (SIU), 2011 IEEE 19th Conference on
Print_ISBN :
978-1-4577-0462-8
DOI :
10.1109/SIU.2011.5929819