Performance comparison of machine learning methods for prognosis of hormone receptor status in breast cancer tissue samples


KALINLI A., Sarikoc F., AKGÜN H., ÖZTÜRK F.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, cilt.110, ss.298-307, 2013 (SCI İndekslerine Giren Dergi) identifier identifier identifier

  • Cilt numarası: 110 Konu: 3
  • Basım Tarihi: 2013
  • Doi Numarası: 10.1016/j.cmpb.2012.12.005
  • Dergi Adı: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
  • Sayfa Sayıları: ss.298-307

Özet

We examined the classification and prognostic scoring performances of several computer methods on different feature sets to obtain objective and reproducible analysis of estrogen receptor status in breast cancer tissue samples.