Artificial Intelligence on Guard of Reproductive Health

Abstract:

According to large-scale international studies, infertility affects about 186 million people around the world. The number of infertile couples increases every year. There are chances to solve this problem by implementing assisted reproductive technologies, mainly in vitro fertilization, into clinical practice. Despite high level of modern reproductive medicine development, only about a third of interventions succeed. Artificial Intelligence technologies are being integrated to make the stages of infertility diagnosis and treatment more accurate and effective. The most progressive directions of current studies are: improvement of quality of biomaterial assessment for IVF, prediction of IVF outcome based on patient data, as well as other methods. This review presents main applications of machine learning algorithms in reproductive medicine, steps involved in creating learning models, some of limitations as well as prospects for implementing these methods into clinical practice.