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Blastocyst

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Does conventional morphological evaluation still play a role in predicting blastocyst formation?

Reproductive biology and endocrinology : RB&E
BACKGROUND: Advanced models including time-lapse imaging and artificial intelligence technologies have been used to predict blastocyst formation. However, the conventional morphological evaluation of embryos is still widely used. The purpose of the p...

Characterization of an artificial intelligence model for ranking static images of blastocyst stage embryos.

Fertility and sterility
OBJECTIVE: To perform a series of analyses characterizing an artificial intelligence (AI) model for ranking blastocyst-stage embryos. The primary objective was to evaluate the benefit of the model for predicting clinical pregnancy, whereas the second...

Inter-centre reliability in embryo grading across several IVF clinics is limited: implications for embryo selection.

Reproductive biomedicine online
RESEARCH QUESTION: What is the intra- and inter-centre reliability in embryo grading performed according to the Istanbul Consensus across several IVF clinics?

Parameters to identify good quality oocytes and embryos in cattle.

Reproduction, fertility, and development
Oocyte/embryo selection methodologies are either invasive or noninvasive and can be applied at various stages of development from the oocyte to cleaved embryos and up to the blastocyst stage. Morphology and the proportion of embryos developing to the...

A machine learning algorithm can optimize the day of trigger to improve in vitro fertilization outcomes.

Fertility and sterility
OBJECTIVE: To determine whether a machine learning causal inference model can optimize trigger injection timing to maximize the yield of fertilized oocytes (2PNs) and total usable blastocysts for a given cohort of stimulated follicles.

Should there be an "AI" in TEAM? Embryologists selection of high implantation potential embryos improves with the aid of an artificial intelligence algorithm.

Journal of assisted reproduction and genetics
PURPOSE: A deep learning artificial intelligence (AI) algorithm has been demonstrated to outperform embryologists in identifying euploid embryos destined to implant with an accuracy of 75.3% (1). Our aim was to evaluate the performance of highly trai...

Embryo selection with artificial intelligence: how to evaluate and compare methods?

Journal of assisted reproduction and genetics
Embryo selection within in vitro fertilization (IVF) is the process of evaluating qualities of fertilized oocytes (embryos) and selecting the best embryo(s) available within a patient cohort for subsequent transfer or cryopreservation. In recent year...

End-to-end deep learning for recognition of ploidy status using time-lapse videos.

Journal of assisted reproduction and genetics
PURPOSE: Our retrospective study is to investigate an end-to-end deep learning model in identifying ploidy status through raw time-lapse video.