AIMC Topic: Fertilization in Vitro

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Automatic grading of human blastocysts from time-lapse imaging.

Computers in biology and medicine
BACKGROUND: Blastocyst morphology is a predictive marker for implantation success of in vitro fertilized human embryos. Morphology grading is therefore commonly used to select the embryo with the highest implantation potential. One of the challenges,...

Personalized prediction of live birth prior to the first in vitro fertilization treatment: a machine learning method.

Journal of translational medicine
BACKGROUND: Infertility has become a global health issue with the number of couples seeking in vitro fertilization (IVF) worldwide continuing to rise. Some couples remain childless after several IVF cycles. Women undergoing IVF face greater risks and...

An artificial neural network for the prediction of assisted reproduction outcome.

Journal of assisted reproduction and genetics
PURPOSE: To construct and validate an efficient artificial neural network (ANN) based on parameters with statistical correlation to live birth, to be used as a comprehensive tool for the prediction of the clinical outcome for patients undergoing ART.

Artificial intelligence and machine learning for human reproduction and embryology presented at ASRM and ESHRE 2018.

Journal of assisted reproduction and genetics
Sixteen artificial intelligence (AI) and machine learning (ML) approaches were reported at the 2018 annual congresses of the American Society for Reproductive Biology (9) and European Society for Human Reproduction and Embryology (7). Nearly every as...

Prediction of implantation after blastocyst transfer in in vitro fertilization: a machine-learning perspective.

Fertility and sterility
OBJECTIVE: To develop a random forest model (RFM) to predict implantation potential of a transferred embryo and compare it with a multivariate logistic regression model (MvLRM), based on data from a large cohort including in vitro fertilization (IVF)...

Are computational applications the "crystal ball" in the IVF laboratory? The evolution from mathematics to artificial intelligence.

Journal of assisted reproduction and genetics
Mathematics rules the world of science. Innovative technologies based on mathematics have paved the way for implementation of novel strategies in assisted reproduction. Ascertaining efficient embryo selection in order to secure optimal pregnancy rate...

Predictive Modeling of Implantation Outcome in an In Vitro Fertilization Setting: An Application of Machine Learning Methods.

Medical decision making : an international journal of the Society for Medical Decision Making
BACKGROUND: Multiple embryo transfers in in vitro fertilization (IVF) treatment increase the number of successful pregnancies while elevating the risk of multiple gestations. IVF-associated multiple pregnancies exhibit significant financial, social, ...

Computer vision for automatic identification of blastocyst structures and blastocyst formation time in In-Vitro Fertilization.

Computers in biology and medicine
Embryo selection is an indispensable step to ensure the success of In-Vitro Fertilization; however, this decision is a time-consuming, laborious, and highly subjective task for embryologists. In the best scenarios, when implanting an embryo of the be...

Predicting time to live birth with deep learning embryo ranking: a novel multiple imputation approach.

Human reproduction (Oxford, England)
STUDY QUESTION: What is the clinical utility of embryo selection algorithms in estimating the time to live birth (TTLB)?

Artificial intelligence for optimal in vitro fertilization morphokinetics.

European journal of obstetrics, gynecology, and reproductive biology
OBJECTIVE: To create an artificial intelligence model able to determine the morphokinetic phases of an embryo by utilizing time-lapse imaging (TLI) videos.