In a recent Fertility and Sterility review, researchers summarize the available evidence on the application of artificial intelligence (AI) and machine learning in sperm selection.
The success rates of ART have remained relatively low globally due to the lack of proper sperm selection. Despite technological advancements, the final sperm selection is primarily performed manually by an embryologist following the World Health Organization (WHO) criteria. Sperm selection is crucial, as a single sperm is required for intracytoplasmic sperm injection (ICSI).
The WHO has provided guidance for proper sperm selection based on the morphology, including sperm head length, presence/absence of vacuole, and circularity, as well as motility. However, embryologists do not have adequate time to assess an entire sperm holistically, which might impact the success of ART. Here, AI could be applied to improve the efficiency of sperm selection.
AI algorithms can standardize and expedite sperm analyses based on the available models. Moreover, sperm morphology in combination with deep learning algorithms, could be evaluated with an accuracy of around 98%. The performance of AI and machine learning algorithms depend on the quality of the training dataset images.
