AIMC Topic: Sperm Injections, Intracytoplasmic
Clear Filters Showing 11 to 20 of 23 articles
Machine learning for sperm selection.
Nature reviews. Urology
May 17, 2021
Infertility rates and the number of couples seeking fertility care have increased worldwide over the past few decades. Over 2.5 million cycles of assisted reproductive technologies are being performed globally every year, but the success rate has rem...
Deep learning early warning system for embryo culture conditions and embryologist performance in the ART laboratory.
Journal of assisted reproduction and genetics
Apr 27, 2021
Staff competency is a crucial component of the in vitro fertilization (IVF) laboratory quality management system because it impacts clinical outcomes and informs the key performance indicators (KPIs) used to continuously monitor and assess culture co...
A robust deep learning-based multiclass segmentation method for analyzing human metaphase II oocyte images.
Computer methods and programs in biomedicine
Jan 19, 2021
BACKGROUND AND OBJECTIVE: The morphology of the human metaphase II (MII) oocyte is an essential indicator of the embryo's potential for developing into a healthy baby in the Intra-Cytoplasmic Sperm Injection (ICSI) process. In this case, characterist...
Artificial intelligence in the IVF laboratory: overview through the application of different types of algorithms for the classification of reproductive data.
Journal of assisted reproduction and genetics
Jul 11, 2020
Over the past years, the assisted reproductive technologies (ARTs) have been accompanied by constant innovations. For instance, intracytoplasmic sperm injection (ICSI), time-lapse monitoring of the embryonic morphokinetics, and PGS are innovative tec...
An artificial neural network for the prediction of assisted reproduction outcome.
Journal of assisted reproduction and genetics
Jun 19, 2019
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.
Prediction of implantation after blastocyst transfer in in vitro fertilization: a machine-learning perspective.
Fertility and sterility
Jan 2, 2019
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)...
Robotic Immobilization of Motile Sperm for Clinical Intracytoplasmic Sperm Injection.
IEEE transactions on bio-medical engineering
Jun 19, 2018
OBJECTIVE: In clinical intracytoplasmic sperm injection (ICSI), a motile sperm must be immobilized before insertion into an oocyte. This paper aims to develop a robotic system for automated tracking, orientation control, and immobilization of motile ...
Applying data mining techniques for increasing implantation rate by selecting best sperms for intra-cytoplasmic sperm injection treatment.
Computer methods and programs in biomedicine
Sep 26, 2016
BACKGROUND AND OBJECTIVE: Aspiration of a good-quality sperm during intracytoplasmic sperm injection (ICSI) is one of the main concerns. Understanding the influence of individual sperm morphology on fertilization, embryo quality, and pregnancy probab...
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
May 19, 2014
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, ...
Artificial intelligence for optimal in vitro fertilization morphokinetics.
European journal of obstetrics, gynecology, and reproductive biology
Jul 1, 2025
OBJECTIVE: To create an artificial intelligence model able to determine the morphokinetic phases of an embryo by utilizing time-lapse imaging (TLI) videos.
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