AIMC Topic: Sperm Motility

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Automated AI for real-time sperm selection in ICSI: reducing variability and studying the role of sperm in embryo development.

Reproductive biology and endocrinology : RB&E
BACKGROUND: The application of Artificial Intelligence (AI) to sperm selection during Intracytoplasmic Sperm Injection (ICSI) procedures represents one of the most innovative advances in assisted reproductive technology (ART). Traditional sperm selec...

Beyond swimming: emerging parameters for predicting the fertility of mouse spermatozoa.

Lab animal
Cryopreservation of spermatozoa can be used as a cost-effective way of preserving the ever-increasing number of genetically modified mouse lines. Nevertheless, discontinuing the breeding of a line or strain is only warranted after the quality control...

Analysis of sperm beating characteristics using microfluidic trapping and machine-learning-based flagellum tracking.

Lab on a chip
Male infertility affects a significant portion of couples worldwide, with standard semen analysis often failing to identify functional deficiencies in sperm performance. This study presents a microfluidic platform for characterizing sperm flagellar b...

3D+t Multifocal Imaging Dataset of Human Sperm.

Scientific data
Understanding human fertility requires dynamic and three-dimensional (3D) analysis of sperm movement, which extends beyond the capabilities of traditional datasets focused primarily on two-dimensional sperm motility or static morphological characteri...

A potential supplemental indication of dipyridamole for contraception: Dipyridamole inhibits mouse sperm fertilization capacity in vitro.

Biochemical and biophysical research communications
The inhibition of sperm cAMP and ATP levels, using an FDA-approved medication, may impair sperm motility and, consequently, fertilization, thus paving the way for the development of a male contraceptive. The objective of this study was to define the ...

Short insemination during conventional in vitro fertilization increases embryo quality.

Andrology
AIM: To compare clinical outcomes using short and long co-incubation protocols in sibling oocytes based on embryo morphokinetic outcomes measured by time-lapse incubator with stratification based on a woman's age and sperm quality.

Deep learning classification method for boar sperm morphology analysis.

Andrology
BACKGROUND: Boar semen quality emphasizes three major criteria: sperm concentration, motility, and morphology. Methods to analyze concentration and motility quickly and objectively readily exist, but few exist for analyzing morphology outside of subj...

Predictability of varicocele repair success: preliminary results of a machine learning-based approach.

Asian journal of andrology
Varicocele is a prevalent condition in the infertile male population. However, to date, which patients may benefit most from varicocele repair is still a matter of debate. The purpose of this study was to evaluate whether certain preintervention sper...

Machine learning approach to assess the association between anthropometric, metabolic, and nutritional status and semen parameters.

Asian journal of andrology
Many lifestyle factors, such as nutritional imbalance leading to obesity, metabolic disorders, and nutritional deficiency, have been identified as potential risk factors for male infertility. The aim of this study was to evaluate the relationship bet...

Identifying predictors of Day 5 blastocyst utilization rate using an artificial neural network.

Reproductive biomedicine online
RESEARCH QUESTION: Can artificial intelligence identify predictors of an increased Day 5 blastocyst utilization rate (D5BUR), which is one of the most informative key performance indicators in an IVF laboratory?