BACKGROUND: Azoospermia is the most severe type of male infertility. This study aimed to identify useful clinical parameters to predict sperm retrieval success. This could assist clinicians in accurately diagnosing and treating patients based on the ...
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...
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...
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 ...
OBJECTIVE: To develop a machine learning algorithm to detect rare human sperm in semen and microsurgical testicular sperm extraction (microTESE) samples using bright-field (BF) microscopy for nonobstructive azoospermia patients.