A Bayesian network model for prediction of low or failed fertilization in assisted reproductive technology based on a large clinical real-world data

• Main Authors: Tian Tian (Author), Fei Kong (Author), Rui Yang (Author), Xiaoyu Long (Author), Lixue Chen (Author), Ming Li (Author), Qin Li (Author), Yongxiu Hao (Author), Yangbo He (Author), Yunjun Zhang (Author), Rong Li (Author), Yuanyuan Wang (Author), Jie Qiao (Author)
• Format: Book
• Published: BMC, 2023-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Abstract Study question To construct prediction models based on the Bayesian network (BN) learning method for the probability of fertilization failure (including low fertilization rate [LRF] and total fertilization failure [TFF]) in assisted reproductive technology (ART) treatment. Summary answer A...