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, sa.3, ss.298-307, 2013 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 110 Sayı: 3
  • Basım Tarihi: 2013
  • Doi Numarası: 10.1016/j.cmpb.2012.12.005
  • Dergi Adı: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.298-307
  • Anahtar Kelimeler: Image processing, Classification, Nucleus segmentation, Estrogen receptor (ER) status evaluation, Breast cancer prognosis, ESTROGEN-RECEPTOR, IMAGE-ANALYSIS, IMMUNOHISTOCHEMISTRY, QUANTIFICATION, MICROARRAYS, CARCINOMAS, EXPRESSION, SECTIONS, SYSTEM, ISSUES
  • Marmara Üniversitesi Adresli: Hayır

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.