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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Autores principales: | Qiuyue Liao, Qi Zhang, Xue Feng, Haibo Huang, Haohao Xu, Baoyuan Tian, Jihao Liu, Qihui Yu, Na Guo, Qun Liu, Bo Huang, Ding Ma, Jihui Ai, Shugong Xu, Kezhen Li |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/22365fca6617491f82115a898e8b8c2e |
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