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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Vydáno v:NPJ Digit Med
Hlavní autoři: 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
Médium: Artigo
Jazyk:Inglês
Vydáno: Nature Publishing Group UK 2019
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Article
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC6550169/
https://ncbi.nlm.nih.gov/pubmed/31304368
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41746-019-0096-y
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