Individualized embryo selection strategy developed by stacking machine learning model for better in vitro fertilization outcomes: an application study
Abstract 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 s...
Main Authors: | Qingsong Xi, Qiyu Yang, Meng Wang, Bo Huang, Bo Zhang, Zhou Li, Shuai Liu, Liu Yang, Lixia Zhu, Lei Jin |
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Format: | Article |
Language: | English |
Published: |
BMC
2021-04-01
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Series: | Reproductive Biology and Endocrinology |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12958-021-00734-z |
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