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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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| Опубликовано в: : | NPJ Digit Med |
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| Главные авторы: | , , , , , , , , , , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Nature Publishing Group UK
2019
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| Предметы: | |
| Online-ссылка: | 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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