The Use of AI Technology and Embryo Imaging for the Diagnosis of Artificial Reproduction Techniques

Following the World Health Organization (WHO), it is estimated that approximately 80 million men and women with childbearing potential around the world need medical assistance due to fertility difficulties, with a rate of approximately 15%, more than three times the population of Taiwan. Similarly, approximately 15% of couples of maternal ages in Taiwan face infertility problems. In the clinical setting, artificial reproduction techniques include artificial insemination and in vitro fertilization (IVF), but the use of IVF is predominant. In vitro fertilization (IVF) is a method of fertilization in which sperm and eggs are extracted and combined through laboratory technology to grow fertilized eggs into embryos and reproduce the fertilized embryo for return to the mother. By establishing a reliable classification and prediction model through deep learning technology, we can assist physicians in embryo selection and systematically select high-quality embryos with high fertility rates, thus reducing manual visual classification errors and improving the success rate of pregnancy.