Abstract：
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.
摘要：
控制性超促排卵（COH）是体外受精-胚胎移植（IVF-ET）的重要组成部分，也是辅助生殖技术（ART）的重要方面。促性腺激素（Gn）的个体起始剂量是COH过程中的关键决定。它对回收的卵母细胞数量有至关重要的影响，ART周期的取消率，和并发症，如卵巢过度刺激综合征（OHSS），以及妊娠结局。如何使临床团队更规范、准确地确定Gn的起始剂量是生殖医学的重要课题。在过去的20年里,世界各地的研究团队已经探索了Gn起始剂量的预测模型。随着人工智能（AI）和深度学习的融合，希望未来有更多适合Gn起始剂量的预测模型。
