Personalized prediction of live birth prior to the first in vitro fertilization treatment: a machine learning method.

ABSTRACT: BACKGROUND:Infertility has become a global health issue with the number of couples seeking in vitro fertilization (IVF) worldwide continuing to rise. Some couples remain childless after several IVF cycles. Women undergoing IVF face greater risks and financial burden. A prediction model to predict the live birth chance prior to the first IVF treatment is needed in clinical practice for patients counselling and shaping expectations. METHODS:Clinical data of 7188 women who underwent their first IVF treatment at the Reproductive Medical Center of Shengjing Hospital of China Medical University during 2014-2018 were retrospectively collected. Machine-learning based models were developed on 70% of the dataset using pre-treatment variables, and prediction performances were evaluated on the remaini

SUBMITTER: Qiu J 

PROVIDER: S-EPMC6757430 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature