Deep learning as a predictive tool for fetal heart pregnancy following time-lapse incubation and blastocyst transfer.
Abstract
We created a deep learning model named IVY, which was an objective and fully automated system that predicts the probability of Fetal Heart pregnancy directly from raw time-lapse videos without the need for any manual morphokinetic annotation or blastocyst morphology assessment.
The high predictive value for embryo implantation obtained by the deep learning model may improve the effectiveness of previous approaches used for time-lapse imaging in embryo selection. This may improve the prioritization of the most viable embryo for a single embryo transfer. The deep learning model may also prove to be useful in providing the optimal order for subsequent transfers of cryopreserved embryos.