Identifying predictors of Day 5 blastocyst utilization rate using an artificial neural network.

Journal: Reproductive biomedicine online
PMID: 37862857

Abstract

RESEARCH QUESTION: Can artificial intelligence identify predictors of an increased Day 5 blastocyst utilization rate (D5BUR), which is one of the most informative key performance indicators in an IVF laboratory?

Authors

  • Munevver Serdarogullari
    Cyprus International University, Faculty of Medicine, Northern Cyprus via Mersin 10, Turkey.
  • Georges Raad
    Al Hadi Laboratory and Medical Centre, Beirut, Lebanon; Faculty of Medicine and Medical Sciences, Holy Spirit University of Kaslik, Jounieh, Lebanon.
  • Zalihe Yarkiner
    Cyprus International University, Faculty of Arts and Sciences, Department of Basic Sciences and Humanities, Northern Cyprus via Mersin 10, Turkey.
  • Marwa Bazzi
    Al Hadi Laboratory and Medical Centre, Beirut, Lebanon.
  • Youmna Mourad
    Al Hadi Laboratory and Medical Centre, Beirut, Lebanon.
  • Sevket Alpturk
    Dogus IVF Centre, Nicosia, Cyprus.
  • Fadi Fakih
    Al Hadi Laboratory and Medical Centre, Beirut, Lebanon.
  • Chadi Fakih
    Al Hadi Laboratory and Medical Centre, Beirut, Lebanon.
  • George Liperis
    Westmead Fertility Centre, Institute of Reproductive Medicine, University of Sydney, Westmead, NSW, Australia. Electronic address: George.liperis@sydney.edu.au.

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