AIMC Topic: Infertility, Male
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Machine learning approach to assess the association between anthropometric, metabolic, and nutritional status and semen parameters.
Asian journal of andrology
Apr 12, 2024
Many lifestyle factors, such as nutritional imbalance leading to obesity, metabolic disorders, and nutritional deficiency, have been identified as potential risk factors for male infertility. The aim of this study was to evaluate the relationship bet...
The human infertility single-cell testis atlas (HISTA): an interactive molecular scRNA-Seq reference of the human testis.
Andrology
Apr 5, 2024
BACKGROUND: Single-cell RNA-seq (scRNA-Seq) has been widely adopted to study gene expression of the human testis. Several datasets of scRNA-Seq from human testis have been generated from different groups processed with different informatics pipelines...
Current Updates on Involvement of Artificial Intelligence and Machine Learning in Semen Analysis.
Medicina (Kaunas, Lithuania)
Feb 6, 2024
: Infertility rates and the number of couples undergoing reproductive care have both increased substantially during the last few decades. Semen analysis is a crucial step in both the diagnosis and the treatment of male infertility. The accuracy of se...
Structures of sperm flagellar doublet microtubules expand the genetic spectrum of male infertility.
Cell
Jun 8, 2023
Sperm motility is crucial for successful fertilization. Highly decorated doublet microtubules (DMTs) form the sperm tail skeleton, which propels the movement of spermatozoa. Using cryo-electron microscopy (cryo-EM) and artificial intelligence (AI)-ba...
Artificial intelligence for sperm selection-a systematic review.
Fertility and sterility
May 24, 2023
Despite the increasing number of assisted reproductive technologies based treatments being performed worldwide, there has been little improvement in fertilization and pregnancy outcomes. Male infertility is a major contributing factor, and sperm eval...
New horizons in human sperm selection for assisted reproduction.
Frontiers in endocrinology
Feb 22, 2023
Male infertility is a commonly encountered pathology that is estimated to be a contributory factor in approximately 50% of couples seeking recourse to assisted reproductive technologies. Upon clinical presentation, such males are commonly subjected t...
Advanced Deep Learning Human Herpes Virus 6 (HHV-6) Molecular Detection in Understanding Human Infertility.
Computational intelligence and neuroscience
Jan 7, 2022
To see if HHV-6 may be a cause of infertility, researchers looked at 18 men and 10 women who had unexplained critical fertility and had at least one prior pregnancy. HHV-6 DNA was discovered in both infertile and fertile peripheral blood mononuclear ...
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...
Machine-learning algorithm incorporating capacitated sperm intracellular pH predicts conventional in vitro fertilization success in normospermic patients.
Fertility and sterility
Jan 15, 2021
OBJECTIVE: To measure human sperm intracellular pH (pH) and develop a machine-learning algorithm to predict successful conventional in vitro fertilization (IVF) in normospermic patients.
Reproductive outcomes predicted by phase imaging with computational specificity of spermatozoon ultrastructure.
Proceedings of the National Academy of Sciences of the United States of America
Jul 20, 2020
The ability to evaluate sperm at the microscopic level, at high-throughput, would be useful for assisted reproductive technologies (ARTs), as it can allow specific selection of sperm cells for in vitro fertilization (IVF). The tradeoff between intrin...
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