AIMC Topic: Sperm Injections, Intracytoplasmic

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Improving outcomes of assisted reproductive technologies using artificial intelligence for sperm selection.

Fertility and sterility
Within the field of assisted reproductive technology, artificial intelligence has become an attractive tool for potentially improving success rates. Recently, artificial intelligence-based tools for sperm evaluation and selection during intracytoplas...

Sperm-cell DNA fragmentation prediction using label-free quantitative phase imaging and deep learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
In intracytoplasmic sperm injection (ICSI), a single sperm cell is selected and injected into an egg. The quality of the chosen sperm and specifically its DNA fragmentation have a significant effect on the fertilization success rate. However, there i...

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.

Machine learning for sperm selection.

Nature reviews. Urology
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
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
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
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
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
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
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 ...