Unpacking the artificial intelligence toolbox for embryo ploidy prediction

Hum Reprod. 2023 Dec 4;38(12):2538-2542. doi: 10.1093/humrep/dead223.

¹ Department of Histology and Embryology, Faculty of Medicine, Cyprus International University, Northern Cyprus, Turkey.
² Westmead Fertility Centre, Institute of Reproductive Medicine, University of Sydney, Westmead, NSW, Australia.
³ HealthPlus Fertility Center, HealthPlus Network of Specialty Centers, Abu Dhabi, United Arab Emirates.
⁴ Biomaterials Cluster, Bernal Institute, University of Limerick, Limerick, Ireland.
⁵ School of Engineering, Faculty of Science and Engineering, University of Limerick, Limerick, Ireland.
⁶ IVF Laboratory, TFP Düsseldorf GmbH, Düsseldorf, Germany.
⁷ IVIRMA Global Research Alliance, Genera, Clinica Valle Giulia, Rome, Italy.
⁸ IRCCS San Raffaele Scientific Institute, Milan, Italy.
⁹ EUGIN Group, R&D, Barcelona, Spain.

No abstract available

Keywords: advanced maternal age; artificial intelligence; embryo assessment; embryo ploidy; machine learning; morphokinetics.

MeSH terms