Artificial intelligence for sperm selection-a systematic review

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 evaluation is a crucial step in diagnosis and treatment. However, embryologists face the daunting task of selecting a single sperm from millions in a sample based on various parameters, which can be time-consuming, subjective, and may even cause damage to the sperm, deeming them un-usable for fertility treatments. Artificial intelligence algorithms have revolutionized the field of medicine, particularly in image process-ing, because of their discerning abilities, efficacy, and reproducibility. Artificial intelligence algorithms have the potential to address the challenges of sperm selection with their large-data processing capabilities and high objectivity. These algorithms could provide valuable assistance to embryologists in sperm analysis and selection. Furthermore, these algorithms could continue to improve over time as larger and more robust datasets become available for their training. (Fertil Sterile 2023;120:24-31. & COPY;2023 by American Society for Reproductive Medicine.)

Automated summary

Despite the increasing use of assisted reproductive technologies worldwide, the success rates of fertilization and pregnancy outcomes have not significantly improved. Male infertility is a major factor, and sperm evaluation is crucial for diagnosis and treatment. However, the process of selecting a single sperm from millions in a sample is challenging and time-consuming. Artificial intelligence algorithms have the potential to revolutionize this process by providing objective and efficient sperm analysis and selection. With further training using larger and more diverse datasets, these algorithms can continue to improve over time.