AIMC Topic: Follicle Stimulating Hormone
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A diagnostic model for polycystic ovary syndrome based on machine learning.
Scientific reports
Mar 21, 2025
Diagnosis of polycystic ovary syndrome remains a challenge. In this study, we propose constructing a diagnostic model of polycystic ovary syndrome by combining anti-Müllerian hormone with steroid hormones and oestrogens, with the aim of providing mor...
Developing a nomogram model for predicting non-obstructive azoospermia using machine learning techniques.
Scientific reports
Feb 14, 2025
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 ...
Understanding the role of hormones in pediatric growth: Insights from a double-debiased machine learning approach.
Steroids
Dec 7, 2024
This study investigates the causal relationships between hormone levels and growth and development of children, focusing specifically on height disparities in cases of dwarfism. Besides utilizing double-debiased machine learning approach, the study i...
Optimizing oocyte yield utilizing a machine learning model for dose and trigger decisions, a multi-center, prospective study.
Scientific reports
Aug 20, 2024
The objective of this study was to evaluate clinical outcomes for patients undergoing IVF treatment where an artificial intelligence (AI) platform was utilized by clinicians to help determine the optimal starting dose of FSH and timing of trigger inj...
Predictability of varicocele repair success: preliminary results of a machine learning-based approach.
Asian journal of andrology
Aug 9, 2024
Varicocele is a prevalent condition in the infertile male population. However, to date, which patients may benefit most from varicocele repair is still a matter of debate. The purpose of this study was to evaluate whether certain preintervention sper...
Development of a machine learning-based prediction model for clinical pregnancy of intrauterine insemination in a large Chinese population.
Journal of assisted reproduction and genetics
May 31, 2024
PURPOSE: This study aimed to evaluate the effectiveness of a random forest (RF) model in predicting clinical pregnancy outcomes from intrauterine insemination (IUI) and identifying significant factors affecting IUI pregnancy in a large Chinese popula...
Immunization against inhibin DNA vaccine as an alternative therapeutic for improving follicle development and reproductive performance in beef cattle.
Frontiers in endocrinology
Feb 15, 2024
The objective of the present study was to investigate the potential role of immunization against INH on follicular development, serum reproductive hormone (FSH, E, and P) concentrations, and reproductive performance in beef cattle. A total of 196 non...
Clinical parameters as predictors for sperm retrieval success in azoospermia: experience from Indonesia.
F1000Research
Dec 6, 2023
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 ...
Detrimental Effects of Saccharum officinarum Juice on Reproductive Functions of Female Wistar Rats.
Nigerian journal of physiological sciences : official publication of the Physiological Society of Nigeria
Jun 30, 2023
Changing dietary compositions have contributed to the growing epidemic of metabolic diseases with serious impacts on several aspects of health, including reproductive health. Saccharum officinarum juice has a natural sweetness that makes the general...
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.
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