The potential of self- supervised learning in embryo selection for IVF success.
review · Level V
Where this comes from
- Record sourced from PubMed, PMID 39081568.
- Also identified by DOI 10.1016/j.patter.2024.101012 and PMC identifier 11284491.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
How to select the "best" embryo for transfer is a long-standing question in clinical <i>in vitro</i> fertilization (IVF). Wang et al. proposed a multi-modal self-supervised learning framework for human embryo selection with a high accuracy and generalization ability.