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Embryo Transfer

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Oocyte and embryo preservation in wild animals: an update.

Cryo letters
The reduction in population genetic diversity due to inbreeding depression and the negative impact of human activity on habitats ultimately generates an extinction debt. Therefore, there is always a dire need to save wild population and to protect bi...

Multifactor Prediction of Embryo Transfer Outcomes Based on a Machine Learning Algorithm.

Frontiers in endocrinology
fertilization-embryo transfer (IVF-ET) technology make it possible for infertile couples to conceive a baby successfully. Nevertheless, IVF-ET does not guarantee success. Frozen embryo transfer (FET) is an important supplement to IVF-ET. Many factor...

Will the introduction of automated ART laboratory systems render the majority of embryologists redundant?

Reproductive biomedicine online
IVF techniques have changed over time with the aim of improving clinical results. Today, embryology is facing a change common to most areas of medicine, the introduction of automation. The use of automated systems in the IVF laboratory is already hap...

An artificial intelligence model (euploid prediction algorithm) can predict embryo ploidy status based on time-lapse data.

Reproductive biology and endocrinology : RB&E
BACKGROUND: For the association between time-lapse technology (TLT) and embryo ploidy status, there has not yet been fully understood. TLT has the characteristics of large amount of data and non-invasiveness. If we want to accurately predict embryo p...

Candidate Circulating Biomarkers of Spontaneous Miscarriage After IVF-ET Identified via Coupling Machine Learning and Serum Lipidomics Profiling.

Reproductive sciences (Thousand Oaks, Calif.)
Spontaneous miscarriage is a common pregnancy complication. Multiple etiologies have been proposed such as genetic aberrations, endocrinology disorder, and immunologic derangement; however, the relevance of circulating lipidomes to the specific condi...

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...

Artificial intelligence model to predict pregnancy and multiple pregnancy risk following in vitro fertilization-embryo transfer (IVF-ET).

Taiwanese journal of obstetrics & gynecology
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...

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)
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?