Development of deep learning algorithms for predicting blastocyst formation and quality by time-lapse monitoring
Liao et al. propose a deep learning model to predict blastocyst formation using TLM videos following the first three days of embryogenesis. The authors develop an ensemble prediction model, STEM and STEM+, which were found to exhibit 78.2% and 71.9% accuracy at predicting blastocyst formation and us...
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| Auteurs principaux: | , , , , , , , , , , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/22365fca6617491f82115a898e8b8c2e |
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