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Prediction of survival outcomes in patients with epithelial ovarian cancer using machine learning methods.

E Sun PaikJeong-Won LeeJeong-Yeol ParkJu-Hyun KimMijung KimTae Joong KimChel Hun ChoiByoung Gie KimDuk Soo BaeSung Wook Seo
Published in: Journal of gynecologic oncology (2019)
Our novel GB-guided classification accurately identified the prognostic subgroups of patients with EOC and showed higher accuracy than the conventional method. This approach would be useful for accurate estimation of individual outcomes of EOC patients.
Keyphrases
  • end stage renal disease
  • ejection fraction
  • newly diagnosed
  • chronic kidney disease
  • machine learning
  • peritoneal dialysis
  • deep learning
  • high resolution
  • patient reported outcomes
  • glycemic control