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...

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Detalles Bibliográficos
Autores principales: Xi, Qingsong, Yang, Qiyu, Wang, Meng, Huang, Bo, Zhang, Bo, Li, Zhou, Liu, Shuai, Yang, Liu, Zhu, Lixia, Jin, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
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

Internet

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

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