Using artificial intelligence to avoid human error in identifying embryos: a retrospective cohort study.

Karissa C HammerVictoria S JiangManoj Kumar Kanakasabapathy Prudhvi Thirumalaraju Hemanth KandulaIrene DimitriadisIrene Souter Charles L Bormann Hadi Shafiee

Published in: Journal of assisted reproduction and genetics (2022)

This study describes an artificial intelligence-based approach for embryo identification. This technology offers a robust witnessing step based on unique morphological features of each embryo. This technology can be integrated with existing imaging systems and laboratory protocols to improve specimen tracking.

Keyphrases

artificial intelligence
machine learning
big data
deep learning
endothelial cells
high resolution
pregnancy outcomes
induced pluripotent stem cells
mass spectrometry