Deep learning as a predictive tool for fetal heart pregnancy following time-lapse incubation and blastocyst transfer.

ABSTRACT:

Study question

Can a deep learning model predict the probability of pregnancy with fetal heart (FH) from time-lapse videos?

Summary answer

We created a deep learning model named IVY, which was an objective and fully automated system that predicts the probability of FH pregnancy directly from raw time-lapse videos without the need for any manual morphokinetic annotation or blastocyst morphology assessment.

What is known already

The contribution of time-lapse imaging in effective embryo selection is promising. Existing algorithms for the analysis of time-lapse imaging are based on morphology and morphokinetic parameters that require subjective human annotation and thus have intrinsic inter-reader and intra-reader variability. Deep learning offers promise for the automat

SUBMITTER: Tran D 

PROVIDER: S-EPMC6554189 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature