Characterization of an artificial intelligence model for ranking static images of blastocyst stage embryos.

Journal: Fertility and sterility
Published Date: Mar 1, 2022

Abstract

OBJECTIVE: To perform a series of analyses characterizing an artificial intelligence (AI) model for ranking blastocyst-stage embryos. The primary objective was to evaluate the benefit of the model for predicting clinical pregnancy, whereas the secondary objective was to identify limitations that may impact clinical use.

Authors

  • Kevin Loewke
    Alife Health Inc., Cambridge, Massachusetts. Electronic address: kloewke@alifehealth.com.
  • Justina Hyunjii Cho
    Alife Health Inc., Cambridge, Massachusetts.
  • Camelia D Brumar
    Alife Health Inc., Cambridge, Massachusetts.
  • Paxton Maeder-York
    Alife Health Inc., Cambridge, Massachusetts.
  • Oleksii Barash
    Reproductive Science Center, San Ramon, California.
  • Jonas E Malmsten
    Weill Cornell Medicine, New York, New York.
  • Nikica Zaninovic
    Ronald O Perelman and Claudia Cohen Center for Reproductive Medicine, Weill Cornell Medicine, 1305 York Ave 6th floor, New York, NY 10021, USA.
  • Denny Sakkas
    Boston IVF - The Eugin Group, Waltham, Massachusetts.
  • Kathleen A Miller
    IVF Florida, Margate, Florida.
  • Michael Levy
    Division of Neurosurgery, Rady's Children's Hospital, San Diego, California, USA.
  • Matthew David VerMilyea
    Ovation Fertility, Austin, Texas.

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