Improved pregnancy prediction performance in an updated deep-learning embryo selection model: a retrospective independent validation study.

Journal: Reproductive biomedicine online
Published Date: Jul 28, 2023

Abstract

RESEARCH QUESTION: What is the effect of increasing training data on the performance of ongoing pregnancy prediction after single vitrified-warmed blastocyst transfer (SVBT) in a deep-learning model?

Authors

  • Satoshi Ueno
    Kato Ladies Clinic, Tokyo, Japan.
  • Jørgen Berntsen
    Vitrolife A/S, Denmark.
  • Tadashi Okimura
    Kato Ladies Clinic, Tokyo, Japan.
  • Keiichi Kato
    Kato Ladies Clinic, Tokyo, Japan. Electronic address: k-kato@towako.net.

Keywords

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