AIMC Topic: Semen Analysis

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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...

Deep feature engineering for accurate sperm morphology classification using CBAM-enhanced ResNet50.

PloS one
BACKGROUND AND OBJECTIVE: Male fertility assessment through sperm morphology analysis remains a critical component of reproductive health evaluation, as abnormal sperm morphology is strongly correlated with reduced fertility rates and poor assisted r...

Use of a sperm morphology assessment standardisation training tool improves the accuracy of novice sperm morphologists.

Scientific reports
Sperm morphology assessment is recognised as a critical, yet variable, test of male fertility. This variability is due in part to the lack of standardised training for morphologists. This study utilised a bespoke 'Sperm Morphology Assessment Standard...

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...

Artificial Intelligence in Andrology: A New Frontier in Male Infertility Diagnosis and Treatment.

Current urology reports
PURPOSE OF REVIEW: Infertility affects approximately 15% of couples globally, with male-factor infertility contributing to about half of these cases. Despite advancements in reproductive medicine, particularly in surgical methods, the prevalence of m...

Developing a nomogram model for predicting non-obstructive azoospermia using machine learning techniques.

Scientific reports
Azoospermia, defined by the absence of sperm in the ejaculate, manifests as obstructive azoospermia (OA) or non-obstructive azoospermia (NOA). Reliable predictive models utilizing biomarkers could aid in clinical decision-making. This study included ...

Enhancing Male Fertility Through AI-Based Management of Varicoceles.

Current urology reports
REVIEW PURPOSE: The clinical management of subclinical and symptomatic varicoceles in male infertility remains challenging. Current guidelines focus on treating men with abnormal semen analyses, but a more precise approach to identify, stratify, and ...

Artificial Intelligence for Clinical Management of Male Infertility, a Scoping Review.

Current urology reports
PURPOSE OF REVIEW: Infertility impacts one in six couples worldwide, with male infertility contributing to approximately half of these cases. However, the causes of infertility remain incompletely understood, and current methods of clinical managemen...

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...