15% of couples have fertility issues. IVF gives them hope but works only 20-30% of the time, can cost a lot of money and be emotionally draining.
Several embryos used to be transferred to maximize chances of birth. It is now accepted that multiple pregnancy can be a risk to both the mother and the children. Thus, only one embryo is typically transferred from the lab to the mother's womb.
Yet, it is tough for doctors to pick the embryo with the highest implantation potential due to a lack of tools to analyse complex multifactorial data.
We use Deep Learning algorithms to analyse a myriad of clinical inputs to detect hidden patterns and predict the embryo with the highest chance of implantation.
This minimizes the number of cycles patients have to go through to become parents and maximizes the ouput of IVF clinics.
With the support of:
