Predicting IVF Outcome: A Proposed Web-based System Using Artificial Intelligence.

Journal: In vivo (Athens, Greece)
PMID: 27381616

Abstract

AIM: To propose a functional in vitro fertilization (IVF) prediction model to assist clinicians in tailoring personalized treatment of subfertile couples and improve assisted reproduction outcome.

Authors

  • Charalampos Siristatidis
    Assisted Reproduction Unit, 3rd Department of Obstetrics and Gynecology, University of Athens, Attikon Hospital, Athens, Greece harrysiri@yahoo.gr.
  • Paraskevi Vogiatzi
    Assisted Reproduction Unit, 3rd Department of Obstetrics and Gynecology, University of Athens, Attikon Hospital, Athens, Greece.
  • Abraham Pouliakis
    2nd Department of Pathology, National and Kapodistrian University of Athens, "Attikon" University Hospital, Athens, Greece.
  • Marialenna Trivella
    Centre for Statistics in Medicine, University of Oxford, Botnar Research Centre, Oxford, U.K.
  • Nikolaos Papantoniou
    Third Department of Obstetrics and Gynecology, University of Athens, Attikon Hospital, Athens, Greece.
  • Stefano Bettocchi
    First Unit of Obstetrics and Gynecology, Department of Biomedical Sciences and Human Oncology, University "Aldo Moro", Bari, Italy.

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