A novel prediction method for lymph node involvement in endometrial cancer: machine learning.

Journal: International journal of gynecological cancer : official journal of the International Gynecological Cancer Society
Published Date: Dec 28, 2018

Abstract

OBJECTIVE: The necessity of lymphadenectomy and the prediction of lymph node involvement (LNI) in endometrial cancer (EC) have been hotly-debated questions in recent years. Machine learning is a broad field that can produce results and estimations. In this study we constructed prediction models for EC patients using the Naïve Bayes machine learning algorithm for LNI prediction.

Authors

  • Emre Günakan
    Department of Obstetrics and Gynecology, University of Medical Sciences, Keçioren Training and Research Hospital, Ankara, Turkey emreg43@hotmail.com.
  • Suat Atan
    Software Developer, Ankara, Turkey.
  • Asuman Nihan Haberal
    Department of Pathology, Başkent University, School of Medicine, Ankara, Turkey.
  • İrem Alyazıcı Küçükyıldız
    Department of Obstetrics and Gynecology, Başkent University, School of Medicine, Ankara, Turkey.
  • Ehad Gökçe
    Department of Obstetrics and Gynecology, Başkent University, School of Medicine, Ankara, Turkey.
  • Ali Ayhan
    Department of Obstetrics and Gynecology, Başkent University, School of Medicine, Ankara, Turkey.

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