Deep-learning model for embryo selection using time-lapse imaging of matched high-quality embryos

Deep-learning model for embryo selection using time-lapse imaging of matched high-quality embryos

Abstract Time-lapse imaging and deep-learning algorithms are promising tools to assess the most viable embryos and improve embryo selection in IVF laboratories. Here, we developed and validated a deep learning model based on self-supervised contrastive learning. The model was developed with a new ap...

Full description

Saved in:
Bibliographic Details
Main Authors: Lisa Boucret, Floris Chabrun, Magalie Boguenet, Pascal Reynier, Pierre-Emmanuel Bouet, Pascale May-Panloup
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Embryo morphokinetics
Artificial intelligence
Time-lapse
Machine learning
Deep learning
Implantation
Online Access:https://doi.org/10.1038/s41598-025-10531-y
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-10531-y

Similar Items