[Interest of iDAScore (intelligent Data Analysis Score) for embryo selection in routine IVF laboratory practice: Results of a preliminary study].

Journal: Gynecologie, obstetrique, fertilite & senologie
Published Date:

Abstract

INTRODUCTION: Embryo selection is a major challenge in ART, especially since the generalization of single embryo transfer, and its optimization could lead to the improvement of clinical results in IVF. Recently, several Artificial Intelligence (AI) models, based on deep-learning such as iDAScore, have been developed. These models, trained on time-lapse videos of embryos with known implantation data, can predict the probability of pregnancy for a given embryo, allowing automatization and standardization in embryo selection.

Authors

  • S Sarandi
    Service d'histologie-embryologie-cytogénétique-CECOS, centre hospitalier universitaire Jean-Verdier, AP-HP, avenue du 14-Juillet, 93140 Bondy, France.
  • Y Boumerdassi
    Service d'histologie-embryologie-cytogénétique-CECOS, centre hospitalier universitaire Jean-Verdier, AP-HP, avenue du 14-Juillet, 93140 Bondy, France; Université Sorbonne Paris Nord, 93000 Bobigny, France.
  • L O'Neill
    Service d'histologie-embryologie-cytogénétique-CECOS, centre hospitalier universitaire Jean-Verdier, AP-HP, avenue du 14-Juillet, 93140 Bondy, France.
  • V Puy
    Service d'histologie-embryologie-cytogénétique-CECOS, centre hospitalier universitaire Jean-Verdier, AP-HP, avenue du 14-Juillet, 93140 Bondy, France; Université Sorbonne Paris Nord, 93000 Bobigny, France.
  • C Sifer
    Service d'histologie-embryologie-cytogénétique-CECOS, centre hospitalier universitaire Jean-Verdier, AP-HP, avenue du 14-Juillet, 93140 Bondy, France. Electronic address: christophe.sifer@aphp.fr.