Application of machine learning in in vitro fertilization

VernacularTitle:机器学习在体外受精-胚胎移植技术中的应用
Author: Yiping YU ¹ ; Yibo GAO ¹ ; Lanlan FANG ¹ ; Yingpu SUN ¹
Author Information

1. 郑州大学第一附属医院生殖医学中心，河南省生殖与遗传重点实验室450052
Publication Type:Journal Article
Keywords: Machine learning; Statistical models; Fertilization in vitro; Pregnancy outcomes; Embryo quality
From: Chinese Journal of Reproduction and Contraception 2021;41(10):883-892
CountryChina
Language:Chinese
Abstract: Based on algorithm, machine learning could dig information from data and learn the rules between data, following by predicting and analyzing new data. Machine learning can be used for the establishment of pregnancy outcome prediction model, as well as for the selection of embryos with the highest implantation potential. This review identified 30 models, among which 28 were based on traditional machine learning and 2 were based on deep learning. Area under the receiver operating characteristic curve (AUC) was adopted for the estimation of model performance. On the whole, models based on traditional algorithm were of low to medium performance (0.600.90). Prediction and estimation models may improve treatment efficiency and standardize embryo selection process.