Open AccessMining of variables from embryo morphokinetics, blastocyst’s morphology and patient parameters: an approach to predict the live birth in the assisted reproduction service
Author(s) -
Dóris Spinosa Chéles,
Eloiza Adriane Dal Molin,
José Celso Rocha,
Marcelo Fábio Gouveia Nogueira
Publication year - 2020
Publication title -
jbra
Language(s) - English
Resource type - Journals
eISSN - 1518-0557
pISSN - 1517-5693
DOI - 10.5935/1518-0557.20200014
Subject(s) - blastocyst , live birth , reproduction , in vitro fertilisation , embryo transfer , embryo , biology , assisted reproductive technology , blastocyst transfer , human fertilization , andrology , pregnancy , embryogenesis , medicine , infertility , anatomy , genetics
Based on growing demand for assisted reproduction technology, improved predictive models are required to optimize in vitro fertilization/intracytoplasmatic sperm injection strategies, prioritizing single embryo transfer. There are still several obstacles to overcome for the purpose of improving assisted reproductive success, such as intra- and inter-observer subjectivity in embryonic selection, high occurrence of multiple pregnancies, maternal and neonatal complications. Here, we compare studies that used several variables that impact the success of assisted reproduction, such as blastocyst morphology and morphokinetic aspects of embryo development as well as characteristics of the patients submitted to assisted reproduction, in order to predict embryo quality, implantation or live birth. Thereby, we emphasize the proposal of an artificial intelligence-based platform for a more objective method to predict live birth.