Reproductive biology and endocrinology : RB&E
Aug 29, 2024
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.
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 ...
Reproductive biology and endocrinology : RB&E
May 22, 2024
BACKGROUND: Deep learning has been increasingly investigated for assisting clinical in vitro fertilization (IVF). The first technical step in many tasks is to visually detect and locate sperm, oocytes, and embryos in images. For clinical deployment o...
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...
: 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...
Infertility is a common disorder affecting 20% of couples worldwide. Furthermore, 40% of all cases are related to male infertility. The first step in the determination of male infertility is semen analysis. The morphology, concentration, and motility...
BACKGROUND AND OBJECTIVE: Infertility affects approximately one in ten couples, and almost half of the infertility cases are due to the malefactor. To diagnose infertility and determine future treatment, a semen analysis is performed. Evaluation of s...
Infertility rates and the number of couples seeking fertility care have increased worldwide over the past few decades. Over 2.5 million cycles of assisted reproductive technologies are being performed globally every year, but the success rate has rem...
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.
We propose a deep learning method based on the Region Based Convolutional Neural Networks (R-CNN) architecture for the evaluation of sperm head motility in human semen videos. The neural network performs the segmentation of sperm heads, while the pro...
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