Development and Validation of a Deep Learning Model to Screen for Trisomy 21 During the First Trimester From Nuchal Ultrasonographic Images.

ABSTRACT:

Importance

Accurate screening of trisomy 21 in the first trimester can provide an early opportunity for decision-making regarding reproductive choices.

Objective

To develop and validate a deep learning model for screening fetuses with trisomy 21 based on ultrasonographic images.

Design, setting, and participants

This diagnostic study used data from all available cases and controls enrolled at 2 hospitals in China between January 2009 and September 2020. Two-dimensional images of the midsagittal plane of the fetal face in singleton pregnancies with gestational age more than 11 weeks and less than 14 weeks were examined. Observers were blinded to subjective fetus nuchal translucency (NT) marker measurements. A convolutional neural network was developed to construct a de

SUBMITTER: Zhang L 

PROVIDER: S-EPMC9214589 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature