Application of machine learning to predict aneuploidy and mosaicism in embryos from in vitro fertilization cycles

ABSTRACT:

BACKGROUND

The factors associated with embryo aneuploidy have been extensively studied. Mostly maternal age and to a lesser extent male factor and ovarian stimulation have been related to the occurrence of chromosomal alterations in the embryo. On the other hand, the main factors that may increase the incidence of embryo mosaicism have not yet been established.

OBJECTIVE

This study aimed to establish a machine learning model that would allow prediction of aneuploidies and mosaicism in embryos conceived via in vitro fertilization, and thus help to determine which variables are associated with these chromosomal alterations.

STUDY DESIGN

The study design was observational and retrospective. A total of 6989 embryos from 2476 cycles of preimplantation genetic testing

SUBMITTER: Ortiz J 

PROVIDER: S-EPMC9574883 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature