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

Journal: Journal of translational medicine

Published Date: Sep 23, 2019

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.

Authors

Jiahui Qiu
Pingping Li

Reproductive Medical Center of Gynecology and Obstetrics Department, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Meng Dong

Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, 100190 Beijing, China.
Xing Xin

Reproductive Medical Center of Gynecology and Obstetrics Department, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Jichun Tan

Reproductive Medical Center of Gynecology and Obstetrics Department, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China. tjczjh@163.com.

Keywords

Adult Algorithms Female Fertilization in Vitro Humans Live Birth Machine Learning Models, Biological Pregnancy Reproducibility of Results

External Resources

View on PubMed Access via DOI PubMed (31547822)

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

Abstract

Authors

Keywords

External Resources

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