卵巢过度刺激综合征
控制性卵巢过度刺激
体外受精
辅助生殖技术
胚胎移植
妇科
医学
妊娠率
怀孕
活产
生殖医学
男科
产科
不育
生物
遗传学
作者
Xuewu Guo,Hong Zhan,Xianghui Zhang,You Zhi Pang,H. Eric Xu,Baolin Zhang,Kaixue Lao,Ping Ding,Yanlin Wang,Liang Han
标识
DOI:10.1080/14647273.2023.2285937
摘要
Controlled ovarian hyperstimulation (COH) is an essential for in vitro fertilization-embryo transfer (IVF-ET) and an important aspect of assisted reproductive technology (ART). Individual starting doses of gonadotropin (Gn) is a critical decision in the process of COH. It has a crucial impact on the number of retrieved oocytes, the cancelling rate of ART cycles, and complications such as ovarian hyperstimulation syndrome (OHSS), as well as pregnancy outcomes. How to make clinical team more standardized and accurate in determining the starting dose of Gn is an important issue in reproductive medicine. In the past 20 years, research teams worldwide have explored prediction models for Gn starting doses. With the integration of artificial intelligence (AI) and deep learning, it is hoped that there will be more suitable predictive model for Gn starting dose in the future.
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