AIMC Topic: Insemination, Artificial

Clear Filters Showing 1 to 10 of 33 articles

Semen collection, semen analysis and artificial insemination in the kākāpō (Strigops habroptilus) to support its conservation.

PloS one
The critically endangered kākāpō (Strigops habroptilus) has suffered population declines due to habitat loss, hunting, and predation. Conservation efforts, including translocation to predator-free islands, have helped increase numbers of this flightl...

Enhancing early identification of high-fertile cattle females using infrared blood serum spectra and machine learning.

Scientific reports
Artificial insemination (AI) success in bovine reproduction is vital for the cattle industry's economic sustainability and for advancing the understanding of reproductive physiology. Identify high-fertile animals' fertility is a complex task due to m...

Development of a machine learning-based prediction model for clinical pregnancy of intrauterine insemination in a large Chinese population.

Journal of assisted reproduction and genetics
PURPOSE: This study aimed to evaluate the effectiveness of a random forest (RF) model in predicting clinical pregnancy outcomes from intrauterine insemination (IUI) and identifying significant factors affecting IUI pregnancy in a large Chinese popula...

Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers and machine learning applications in dairy cattle.

Theriogenology
This study aimed to compare the accuracy of IFN-τ stimulated gene abundance (ISGs) in peripheral blood mononuclear cells (PBMCs), CL blood perfusion by Doppler ultrasound (Doppler-US), plasma concentration of P4 on Day 21 and pregnancy-associated gly...

Artificial intelligence in the service of intrauterine insemination and timed intercourse in spontaneous cycles.

Fertility and sterility
OBJECTIVE: To develop a machine learning model designed to predict the time of ovulation and optimal fertilization window for performing intrauterine insemination or timed intercourse (TI) in natural cycles.

Can methods of artificial intelligence aid in optimizing patient selection in patients undergoing intrauterine inseminations?

Journal of assisted reproduction and genetics
PURPOSE: AI and its machine learning algorithms have proven useful in several fields of medicine, including medically assisted reproduction. The purpose of the study was to construct several predictive models based on clinical data and select the bes...

Deep Learning Based Evaluation of Spermatozoid Motility for Artificial Insemination.

Sensors (Basel, Switzerland)
We propose a deep learning method based on the Region Based Convolutional Neural Networks (R-CNN) architecture for the evaluation of sperm head motility in human semen videos. The neural network performs the segmentation of sperm heads, while the pro...

Transcriptome analysis and identification of genes associated with chicken sperm storage duration.

Poultry science
The sperm storage tubules located in the mucosal folds of the uterovaginal junction (UVJ) are the primary site of sperm storage in chicken hens after natural mating or artificial insemination (AI). The short-term sperm storage (24 h after mating or A...

Low-Invasive Cell Injection based on Rotational Microrobot.

Advanced biosystems
The advancement of cell injections has created a need for accurate, efficient, and low-invasive injections. However, the conventional approaches to reduce cell damage during penetration, mainly optimization of micropipette tips and vision-based autom...