Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization

Visual morphology assessment is routinely used for evaluating of embryo quality and selecting human blastocysts for transfer after in vitro fertilization (IVF). However, the assessment produces different results between embryologists and as a result, the success rate of IVF remains low. To overcome...

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Detalles Bibliográficos
Autores principales: Khosravi, Pegah, Kazemi, Ehsan, Zhan, Qiansheng, Malmsten, Jonas E., Toschi, Marco, Zisimopoulos, Pantelis, Sigaras, Alexandros, Lavery, Stuart, Cooper, Lee A. D., Hickman, Cristina, Meseguer, Marcos, Rosenwaks, Zev, Elemento, Olivier, Zaninovic, Nikica, Hajirasouliha, Iman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6550169/
https://www.ncbi.nlm.nih.gov/pubmed/31304368
http://dx.doi.org/10.1038/s41746-019-0096-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6550169/
https://www.ncbi.nlm.nih.gov/pubmed/31304368
http://dx.doi.org/10.1038/s41746-019-0096-y

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