The utility of artificial neural networks and classification and regression trees for the prediction of endometrial cancer in postmenopausal women.

Journal: Public health
Published Date: Aug 24, 2018

Abstract

OBJECTIVE: Artificial neural networks (ANNs) and classification and regression trees (CARTs) have been previously used for the prediction of cancer in several fields. In our study, we aim to investigate the diagnostic accuracy of three different methodologies (i.e. logistic regression, ANNs and CARTs) for the prediction of endometrial cancer in postmenopausal women with vaginal bleeding or endometrial thickness ≥5 mm, as determined by ultrasound examination.

Authors

  • V Pergialiotis
    3rd Department of Obstetrics and Gynecology, National and Kapodistrian University of Athens, Athens, Attikon University Hospital, Greece. Electronic address: pergialiotis@yahoo.com.
  • A Pouliakis
    2nd Department of Pathology, National and Kapodistrian University of Athens, Attikon University Hospital, Athens, Greece.
  • C Parthenis
    3rd Department of Obstetrics and Gynecology, National and Kapodistrian University of Athens, Athens, Attikon University Hospital, Greece.
  • V Damaskou
    3rd Department of Obstetrics and Gynecology, National and Kapodistrian University of Athens, Athens, Attikon University Hospital, Greece.
  • C Chrelias
    3rd Department of Obstetrics and Gynecology, National and Kapodistrian University of Athens, Athens, Attikon University Hospital, Greece.
  • N Papantoniou
    3rd Department of Obstetrics and Gynecology, National and Kapodistrian University of Athens, Athens, Attikon University Hospital, Greece.
  • I Panayiotides
    2nd Department of Pathology, National and Kapodistrian University of Athens, Attikon University Hospital, Athens, Greece.

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