Using Deep Learning in a Monocentric Study to Characterize Maternal Immune Environment for Predicting Pregnancy Outcomes in the Recurrent Reproductive Failure Patients

Using Deep Learning in a Monocentric Study to Characterize Maternal Immune Environment for Predicting Pregnancy Outcomes in the Recurrent Reproductive Failure Patients

Recurrent reproductive failure (RRF), such as recurrent pregnancy loss and repeated implantation failure, is characterized by complex etiologies and particularly associated with diverse maternal factors. It is currently believed that RRF is closely associated with the maternal environment, which is,...

Full description

Bibliographic Details
Main Authors: Chunyu Huang, Zheng Xiang, Yongnu Zhang, Dao Shen Tan, Chun Kit Yip, Zhiqiang Liu, Yuye Li, Shuyi Yu, Lianghui Diao, Lap Yan Wong, Wai Lim Ling, Yong Zeng, Wenwei Tu
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-04-01
Series:Frontiers in Immunology
Subjects:
artificial intelligence
recurrent reproductive failure
reproductive immunology
sparse coding
assisted reproductive technology
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2021.642167/full

Internet

https://www.frontiersin.org/articles/10.3389/fimmu.2021.642167/full

Similar Items