AI is employed in fertility to assist in reproductive health and treatment. It utilizes machine learning algorithms and data analysis to predict fertility outcomes, optimize treatment protocols, and provide personalized insights for individuals and couples seeking to conceive.
Researchers developed a method using UAV-based remote sensing and machine learning to evaluate soybean drought tolerance, tested on hundreds of genotypes across varying conditions. This high-throughput approach, validated against manual measurements, offers rapid and accurate drought assessment.
Researchers have developed an AI application named 'SpermSearch', which can swiftly and accurately locate sperm in severely infertile men, potentially improving their chances of fathering children. This tool optimizes the lengthy and challenging process of sperm identification, and is a promising breakthrough in fertility treatments for men with non-obstructive azoospermia (NOA).
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