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Embryo Transfer

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Seeking arrangements: cell contact as a cleavage-stage biomarker.

Reproductive biomedicine online
RESEARCH QUESTION: What can three-dimensional cell contact networks tell us about the developmental potential of cleavage-stage human embryos?

An ultrasound-based deep learning radiomic model combined with clinical data to predict clinical pregnancy after frozen embryo transfer: a pilot cohort study.

Reproductive biomedicine online
RESEARCH QUESTION: Can a multi-modal fusion model based on ultrasound-based deep learning radiomics combined with clinical parameters provide personalized evaluation of endometrial receptivity and predict the occurrence of clinical pregnancy after fr...

Deep learning analysis of endometrial histology as a promising tool to predict the chance of pregnancy after frozen embryo transfers.

Journal of assisted reproduction and genetics
PURPOSE: Endometrial histology on hematoxylin and eosin (H&E)-stained preparations provides information associated with receptivity. However, traditional histological examination by Noyes' dating method is of limited value as it is prone to subjectiv...

Artificial intelligence in the in vitro fertilization laboratory: a review of advancements over the last decade.

Fertility and sterility
The integration of artificial intelligence (AI) and deep learning algorithms into medical care has been the focus of development over the last decade, particularly in the field of assisted reproductive technologies and in vitro fertilization (IVF). W...

External validation of a model for selecting day 3 embryos for transfer based upon deep learning and time-lapse imaging.

Reproductive biomedicine online
RESEARCH QUESTION: Could objective embryo assessment using iDAScore Version 2.0 perform as well as conventional morphological assessment?

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

Reproductive biomedicine online
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?

Interpretable artificial intelligence-assisted embryo selection improved single-blastocyst transfer outcomes: a prospective cohort study.

Reproductive biomedicine online
RESEARCH QUESTION: What is the pregnancy and neonatal outcomes of an interpretable artificial intelligence (AI) model for embryo selection in a prospective clinical trial?

Discard or not discard, that is the question: an international survey across 117 embryologists on the clinical management of borderline quality blastocysts.

Human reproduction (Oxford, England)
STUDY QUESTION: Do embryologists from different European countries agree on embryo disposition decisions ('use' or 'discard') about Day 7 (>144 h post-insemination) and/or low-quality blastocysts (LQB;

Correlations between a deep learning-based algorithm for embryo evaluation with cleavage-stage cell numbers and fragmentation.

Reproductive biomedicine online
RESEARCH QUESTION: Do cell numbers and degree of fragmentation in cleavage-stage embryos, assessed manually, correlate with evaluations made by deep learning algorithm model iDAScore v2.0?

Artificial intelligence-powered assisted ranking of sibling embryos to increase first cycle pregnancy rate.

Reproductive biomedicine online
RESEARCH QUESTION: Could EMBRYOLY, an artificial intelligence embryo evaluation tool, assist embryologists to increase first cycle pregnancy rate and reduce cycles to pregnancy for patients?