Abstract
As a disease that seriously affects the health of men and women of childbearing age, the incidence of infertility is increasing worldwide, and the popularization of assisted reproductive technology (ART) is expected to improve the situation. However, invitro fertilization and embryo transfer (IVF) success rates are only about 50%, and IVF success rates are affected by a number of factors. For example, semen quality, endometrial thickness, fallopian tube patency, embryo selection and transplantation, uterine microenvironment, etc., and the treatment process of IVF is highly dependent on the clinical experience of embryologists, and there is a lack of objective and unified evaluation criteria. Artificial intelligence (AI) is ideally suited to processing and analyzing large, dynamic temporal data sets to assist physicians in making more objective and precise decisions, thereby improving IVF success. At present, artificial intelligence technology using different types of algorithms has been used for sperm classification, oocyte and embryo selection, and prediction of embryo development after implantation, etc. The application of AI in the field of assisted reproduction is expected to improve infertility diagnosis results and increase the pregnancy rate and live birth rate of ART, but there are still certain controversies in privacy, safety and other aspects.In the future, with the accumulation of high-quality datasets, algorithm optimization and the advancement of imaging technology, AI is expected to increase the success rate of ART by selecting higher-quality sperm and oocytes, as well as embryos with greater developmental potential. This will bring significant innovation to the field of reproductive medicine and the entire healthcare sector, while also reducing treatment costs.