AIMC Topic: Embryo Transfer
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Risk factors for recurrent implantation failure as defined by the European Society for Human Reproduction and Embryology.
Human reproduction (Oxford, England)
Jun 1, 2025
STUDY QUESTION: What are the unrecognized risk factors for recurrent implantation failure (RIF) as defined in the ESHRE recommendation?
A deep learning tissue classifier based on differential co-expression genes predicts the pregnancy outcomes of cattle†.
Biology of reproduction
Mar 16, 2025
Economic losses in cattle farms are frequently associated with failed pregnancies. Some studies found that the transcriptomic profiles of blood and endometrial tissues in cattle with varying pregnancy outcomes display discrepancies even before artifi...
Artificial intelligence-driven analysis of embryo morphokinetics in singleton, twin, and triplet pregnancies.
Human reproduction (Oxford, England)
Mar 1, 2025
In recent years, the transfer of more than one embryo has become less frequent to diminish multiple pregnancies. Even so, there is still a risk of one embryo splitting into two or even three. This report presents the case of a triamniotic monochorion...
Ethics of artificial intelligence in embryo assessment: mapping the terrain.
Human reproduction (Oxford, England)
Feb 1, 2025
Artificial intelligence (AI) has the potential to standardize and automate important aspects of fertility treatment, improving clinical outcomes. One promising application of AI in the fertility clinic is the use of machine learning (ML) tools to ass...
The 'golden fleece of embryology' eludes us once again: a recent RCT using artificial intelligence reveals again that blastocyst morphology remains the standard to beat.
Human reproduction (Oxford, England)
Jan 1, 2025
Grading of blastocyst morphology is used routinely for embryo selection with good outcomes. A lot of effort has been placed in IVF to search for the prize of selecting the most viable embryo to transfer ('the golden fleece of embryology'). To improve...
Time will tell: time-lapse technology and artificial intelligence to set time cut-offs indicating embryo incompetence.
Human reproduction (Oxford, England)
Dec 1, 2024
STUDY QUESTION: Can more reliable time cut-offs of embryo developmental incompetence be generated by combining time-lapse technology (TLT), artificial intelligence, and preimplantation genetics screening for aneuploidy (PGT-A)?
[Application of the blastomere count variations "skip value" in the embryo AI assessment].
Zhonghua fu chan ke za zhi
Jul 25, 2024
To explore the correlation between blastomere count variations "skip value" which extracted from by time-lapse technology (TLT) combined with artificial intelligence (AI) and morphological features of in vitro fertilization (IVF) embryo, and to test...
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)
Oct 3, 2023
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;
A hybrid artificial intelligence model leverages multi-centric clinical data to improve fetal heart rate pregnancy prediction across time-lapse systems.
Human reproduction (Oxford, England)
Apr 3, 2023
STUDY QUESTION: Can artificial intelligence (AI) algorithms developed to assist embryologists in evaluating embryo morphokinetics be enriched with multi-centric clinical data to better predict clinical pregnancy outcome?
Artificial intelligence model to predict pregnancy and multiple pregnancy risk following in vitro fertilization-embryo transfer (IVF-ET).
Taiwanese journal of obstetrics & gynecology
Sep 1, 2022
OBJECTIVE: To decrease multiple pregnancy risk and sustain optimal pregnancy chance by choosing suitable number of embryos during transfer, this study aims to construct artificial intelligence models to predict the pregnancy outcome and multiple preg...
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