A machine learning approach to predict self-efficacy in breast cancer survivors.

Journal: BMC medical informatics and decision making
Published Date: Aug 19, 2025

Abstract

PURPOSE: To determine predictors of self-efficacy in breast cancer survivors and identify vulnerable groups.

Authors

  • İsmail Toygar
    Muğla Sıtkı Koçman University, Fethiye Faculty of Health Sciences , Fethiye, Muğla, Türkiye. ismail.toygar1@gmail.com.
  • Su Özgür
    Ege University Faculty of Medicine, Department of Biostatistics and Medical Informatics, Turkey.
  • Gülcan Bağçivan
    Koç University Faculty of Nursing, İstanbul, 34010, Turkey.
  • Ezgi Karaçam
    Dr Sadi Konuk Training and Research Hospital, İstanbul, 30110, Turkey.
  • Hilal Benzer
    Hasan Kalyoncu University Vocational School, Şahinbey, Gaziantep, 27410, Turkey.
  • Ferda Akyüz Özdemir
    Fethiye Faculty of Health Sciences, Muğla Sıtkı Koçman University, Fethiye, Muğla, 48330, Turkey.
  • Halise Taşkın Duman
    Fethiye Faculty of Health Sciences, Muğla Sıtkı Koçman University, Fethiye, Muğla, 48330, Turkey.
  • Özlem Ovayolu
    Gaziantep University Faculty of Health Sciences, Şahinbey, Gaziantep, 27410, Turkey.

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