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...

Descripción completa

Guardado en:
Detalles Bibliográficos
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
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Acceso en línea:https://doaj.org/article/22365fca6617491f82115a898e8b8c2e
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares