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Individualized embryo selection strategy developed by stacking machine learning model for better in vitro fertilization outcomes: an application study
BACKGROUND: To minimize the rate of in vitro fertilization (IVF)- associated multiple-embryo gestation, significant efforts have been made. Previous studies related to machine learning in IVF mainly focused on selecting the top-quality embryos to improve outcomes, however, in patients with sub-optim...
| Autores principales: | , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8020549/ https://www.ncbi.nlm.nih.gov/pubmed/33820565 http://dx.doi.org/10.1186/s12958-021-00734-z |