In vitro fertilization (IVF) is a widely used assisted reproductive technology that involves the surgical retrieval of eggs from the ovary, followed by their fertilization with sperm in a laboratory setting. After a brief incubation period, embryologists select the most promising blastocyst, a very early-stage embryo, for implantation in the uterus. The success rates of IVF procedures vary significantly based on factors such as the woman’s age. According to data from the Society for Assisted Reproductive Technology, the likelihood of a live birth from a single IVF attempt is less than 50% for women under 35 and drops to less than 10% for women aged 41-42.
Therefore, it has been postulated that AI can benefit IVF in the selection of embryos in several ways.
Firstly, AI can analyze genetic data from embryos to identify those with the highest likelihood of successful implantation and healthy development. This can help improve pregnancy outcomes and reduce the risk of genetic disorders.
Secondly, AI algorithms can analyze large datasets of IVF outcomes to identify patterns and factors that contribute to successful pregnancies. This information can be used to predict the likelihood of success for individual embryos and guide embryo selection.
Thirdly, AI can analyze time-lapse videos of developing embryos to assess their quality and viability. By monitoring various parameters such as cell division rates and morphological changes, AI algorithms can provide insights into embryo development and help select the most promising embryos for transfer.
Fourthly, AI can assist in generating a personalized protocol. It can generate an integrated report for each patient. Patient specific data, such as age and medical history could provide personalized recommendations for embryo selection, thereby increasing the success for each patient.
Fifth, AI can help reduce the risk of multiple pregnancies, which are associated with higher complications for both the mother and the babies. By accurately predicting the viability of embryos, AI can guide the transfer of a single embryo, minimizing the chances of multiple pregnancies.
Sixth, AI can automate and streamline the embryo selection process, saving time and resources for fertility clinics. This can help improve the overall efficiency of IVF treatments and make them more accessible to a larger number of patients.
The final clinical decision for embryo selection should be made by healthcare professionals based on a comprehensive evaluation of various factors and individual patient circumstances.
