Predicting cumulative live birth rate for patients undergoing in vitro fertilization(IVF)/intracytoplasmic sperm injection(ICSI)for tubal and male infertility:a machine learning approach using XGBoost  

作　　者：Zhiyan Chen Duoduo Zhang Jingran Zhen Zhengyi Sun Qi Yu 

机构地区：[1]Department of Obstetrics and Gynecology,National Clinical Research Center for Obstetric&Gynecologic Diseases,Peking Union Medical College Hospital,Chinese Academy of Medical Sciences&Peking Union Medical College,Beijing 100730,China

出　　处：《Chinese Medical Journal》2022年第8期997-999,共3页中华医学杂志（英文版）

摘　　要：To the Editor:Confronted with increasing infertility worldwide,this decade has witnessed a sharp rise in the utilization of artificial reproduction technology(ART).111 Nevertheless,the success rate of in vitro fertilization(IVF)/intracytoplasmic sperm injection(ICSI)depends on many factors.Moreover,patients receiving ART not only incur high expenses but also an increased risk of severe side effects,such as ovarian hyperstimulation syndrome,infection,and multiple pregnancies.121 Consequently,the accurate prediction of ART outcomes has attracted tremendous interest.

关 键 词：injection PATIENTS INFERTILITY 

分 类 号：R698.2[医药卫生—泌尿科学]