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Fertility

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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...

The marital and fertility sentiment orientation of Chinese women and its influencing factors - An analysis based on natural language processing.

PloS one
BACKGROUND: With the evolution of China's social structure and values, there has been a shift in attitudes towards marriage and fertility, with an increasing number of women holding diverse perspectives on these matters. In order to better comprehend...

Non-destructive prediction of fertility and sex in chicken eggs using the short wave near-infrared region.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The objective of this study was to evaluate the ability of a handheld near-infrared device (900-1600 nm) to predict fertility and sex (male and female) traits in-ovo. The NIR reflectance spectra of the egg samples were collected on days 0, 7, 14 and ...

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...

FertilitY Predictor-a machine learning-based web tool for the prediction of assisted reproduction outcomes in men with Y chromosome microdeletions.

Journal of assisted reproduction and genetics
PURPOSE: Y chromosome microdeletions (YCMD) are a common cause of azoospermia and oligozoospermia in men. Herein, we developed a machine learning-based web tool to predict sperm retrieval rates and success rates of assisted reproduction (ART) in men ...

The application of machine learning approaches to classify and predict fertility rate in Ethiopia.

Scientific reports
Integrating machine learning (ML) models into healthcare systems is a rapidly evolving field with the potential to revolutionize care delivery. This study aimed to classify fertility rates and identify significant predictors using ML models among rep...

Prediction and unsupervised clustering of fertility intention among migrant workers based on machine learning: a cross-sectional survey from Henan, China.

BMC public health
BACKGROUND: Although China has implemented multiple policies to encourage childbirth, the results have been underwhelming. Migrant workers account for a considerable proportion of China's population, most of whom are of childbearing age. However, few...

Machine learning analysis of the relationships between traumatic childbirth experience with positive and negative fertility motivations in Iran in a community-based sample.

Reproductive health
BACKGROUND: Psychologically traumatic childbirth leads to short and long-term negative impacts on a woman's health and impacts future reproductive decisions. Considering the importance of fertility growth and strengthening positive fertility motivati...

Visualized hysteroscopic artificial intelligence fertility assessment system for endometrial injury: an image-deep-learning study.

Annals of medicine
OBJECTIVE: Asherman's syndrome (AS) is a significant cause of subfertility in women from developing countries. Over 80% of AS cases in these regions are linked to dilation and curettage (D&C) procedures following pregnancy. The incidence of AS in pat...

A deep learning approach to understanding controlled ovarian stimulation and in vitro fertilization dynamics.

Scientific reports
Infertility, recognized by the World Health Organization (WHO) as a disease affecting the male or female reproductive system, presents a global challenge due to its impact on one in six individuals worldwide. Given the high prevalence of infertility ...