Breast Cancer Classification Using Deep Learning


Ilhan U., Uyar K., Iseri E. İ.

14th International Conference on Applications of Fuzzy Systems, Soft Computing, and Artificial Intelligence Tools, ICAFS 2020, Budva, Karadağ, 27 - 28 Ağustos 2020, cilt.1306, ss.709-714, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 1306
  • Doi Numarası: 10.1007/978-3-030-64058-3_88
  • Basıldığı Şehir: Budva
  • Basıldığı Ülke: Karadağ
  • Sayfa Sayıları: ss.709-714
  • Anahtar Kelimeler: Breast cancer, Classification, Deep learning, Wisconsin (Diagnostic) data set
  • Orta Doğu Teknik Üniversitesi Kuzey Kıbrıs Kampüsü Adresli: Hayır

Özet

Cancer in any form is one of the most deadly illnesses in the world. Scientists are investigating into this disease and developing methods and treatments to fight it. The recent surveys show that breast cancer is also one of the major causes of mortality rate among female population around the world. Breast cancer’s definition may be explained as some old cells that aggressively grow out of control to form a population of a harmful mass in the breast tissue. Eventually, as a result they lead to the formation a malignant tumor. Deep learning (DL) that is the subfield of machine learning algorithms provides a powerful tool to help experts to analyze, model and make sense of complex clinical data across a broad range of medical applications. The aim of this study is to develop an efficient system to classify breast tumors as malignant and benign. This system is divided in two stages. The first stage is the normalization of the data. The second stage is the classification of tumors. The accuracy of the approach is 98.42%. The overall result showed that the DL outperformed the previous studies where the same data set was used.