AIMC Topic: Azoospermia
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Construction and external validation of a 5-gene random forest model to diagnose non-obstructive azoospermia based on the single-cell RNA sequencing of testicular tissue.
Aging
Nov 4, 2021
Non-obstructive azoospermia (NOA) is among the most severe factors for male infertility, but our understandings of the latent biological mechanisms remain insufficient. The single-cell RNA sequencing (scRNA-seq) data of 432 testicular cells isolated ...
A method for utilizing automated machine learning for histopathological classification of testis based on Johnsen scores.
Scientific reports
May 10, 2021
We examined whether a tool for determining Johnsen scores automatically using artificial intelligence (AI) could be used in place of traditional Johnsen scoring to support pathologists' evaluations. Average precision, precision, and recall were asses...
Artificial Neural Network for the Prediction of Chromosomal Abnormalities in Azoospermic Males.
Urology journal
May 3, 2018
PURPOSE: To evaluate whether an artifical neural network helps to diagnose any chromosomal abnormalities in azoospermic males.
[Artificial intelligence: to a better predictive strategy for testicular sperm extraction outcome in azoospermia].
Annales de biologie clinique
Jun 5, 2024
Azoospermia, defined as the absence of sperm in the semen, is found in 10-15 % of infertile patients. Two-thirds of these cases are caused by impaired spermatogenesis, known as non-obstructive azoospermia (NOA). In this context, surgical sperm extrac...
[Exploring the mechanisms of ferroptosis in non-obstructive azoospermia based on bioinformatics and machine learning].
Zhonghua nan ke xue = National journal of andrology
Oct 1, 2023
OBJECTIVE: To explor the potential mechanisms of ferroptosis involvement in non-obstructive azoospermia based on bioinformatics and machine learning methods.
A preliminary study of sperm identification in microdissection testicular sperm extraction samples with deep convolutional neural networks.
Asian journal of andrology
Jan 1, 2021
Sperm identification and selection is an essential task when processing human testicular samples for in vitro fertilization. Locating and identifying sperm cell(s) in human testicular biopsy samples is labor intensive and time consuming. We developed...
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