Correlations between a deep learning-based algorithm for embryo evaluation with cleavage-stage cell numbers and fragmentation
Author:
Publisher
Elsevier BV
Subject
Developmental Biology,Reproductive Medicine,Obstetrics and Gynecology
Reference24 articles.
1. The istanbul consensus workshop on embryo assessment: Proceedings of an expert meeting;Hum Reprod,2011
2. Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequences;Berntsen;PLoS One,2022
3. Towards automation in ivf: Pre-clinical validation of a deep learning-based embryo grading system during pgt-a cycles;Cimadomo;J Clin Med,2023
4. A stepwise approach to move from a cleavage-stage to a blastocyst-stage transfer policy for all patients in the ivf clinic;De Croo;Hum Reprod Open,2020
5. Cumulative live birth rates after fresh and vitrified cleavage-stage versus blastocyst-stage embryo transfer in the first treatment cycle;De Vos;Hum Reprod,2016
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