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Semen Analysis

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Artificial intelligence model for the assessment of unstained live sperm morphology.

Reproduction & fertility
ABSTRACT: Traditional sperm morphology assessment requires staining and high magnification (100×), rendering sperm unsuitable for further use. We aimed to determine whether an in-house artificial intelligence (AI) model could reliably assess normal s...

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...

Multimodal distribution and its impact on the accurate assessment of spermatozoa morphological data: Lessons from machine learning.

Animal reproduction science
Objective assessment of sperm morphology is an essential component for assessing ejaculate quality. Due to economic limitations, investigators often divert to conducting observational studies instead of experimental ones, which provide the strongest ...

The prediction of semen quality based on lifestyle behaviours by the machine learning based models.

Reproductive biology and endocrinology : RB&E
PURPOSE: To find the machine learning (ML) method that has the highest accuracy in predicting the semen quality of men based on basic questionnaire data about lifestyle behavior.

[Application of Artificial Intelligence in Sperm Quality Analysis and Sperm Screening].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
Infertility is a global health issue, and more and more people are hoping to have babies by means of assisted reproductive technology. However, there are still many challenges in fertilization and pregnancy outcomes. Sperm quality is a key factor aff...

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...

Current and Future Applications of Artificial Intelligence to Diagnose and Treat Male Infertility.

Advances in experimental medicine and biology
Artificial intelligence (AI) models are being increasingly applied to modern medicine. Within the field of urology, reproductive urology specifically offers many opportunities to utilize this advanced computational technology for diagnostic and thera...

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 ...