Application of machine learning techniques for predicting survival in ovarian cancer.

Journal: BMC medical informatics and decision making
Published Date: Dec 30, 2022

Abstract

BACKGROUND: Ovarian cancer is the fifth leading cause of mortality among women in the United States. Ovarian cancer is also known as forgotten cancer or silent disease. The survival of ovarian cancer patients depends on several factors, including the treatment process and the prognosis.

Authors

  • Amir Sorayaie Azar
    Department of Computer Engineering, Urmia University, Urmia, Iran.
  • Samin Babaei Rikan
    Department of Computer Engineering, Urmia University, Urmia, Iran.
  • Amin Naemi
    Centre of Health Informatics and Technology, The Maersk Mc-Kinney Moller, Institute, University of Southern Denmark, Odense, Denmark.
  • Jamshid Bagherzadeh Mohasefi
    Department of Computer Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran; Department of Electrical and Computer Engineering, Urmia University, Urmia, Iran. Electronic address: j.bagherzadeh@urmia.ac.ir.
  • Habibollah Pirnejad
    Department of Health Information Technology, Urmia University of Medical Sciences, Urmia, Iran; Patient Safety Research Center, Urmia University of Medical Sciences, Urmia, Iran; Erasmus School of Health Policy & Management (ESHPM), Erasmus University Rotterdam, Rotterdam, the Netherlands.
  • Matin Bagherzadeh Mohasefi
    School of Medicine, University of Bari-Aldo Moro, Bari, Italy.
  • Uffe Kock Wiil
    Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Denmark.

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