An ensemble of neural networks for breast cancer diagnosis

Yavuz E., Eyupoglu C., ŞANVER U., YAZICI R.

2nd International Conference on Computer Science and Engineering, UBMK 2017, Antalya, Türkiye, 5 - 08 Ekim 2017, ss.538-543 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/ubmk.2017.8093456
  • Basıldığı Şehir: Antalya
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.538-543
  • Anahtar Kelimeler: breast cancer diagnosis, expert system, radial basis function network, generalized regression neural network, feed forward neural network
  • İstanbul Ticaret Üniversitesi Adresli: Evet

Özet

Since breast cancer is a common disease in society all over the world, early diagnosis is of vital importance in order to treat patients before it reaches an irreversible phase. Expert systems are being developed to make it easier to diagnose the disease. In this study, an ensemble of neural networks named radial basis function network (RBFN), generalized regression neural network (GRNN) and feed forward neural network (FFNN) is implemented to separate breast cancer data samples into benign/malignant classes. The utilities of these common methods and the proposed hybrid model which is a combination of these methods are explored and their performances are comparatively presented. The experimental results on Wisconsin Diagnostic Breast Cancer (WDBC) dataset have proven that the proposed method presents a promise for diagnosis of breast cancer. The proposed model can be used as a tool to assist medical specialists in making their decision on the disease.