Machine learning-enhanced noninvasive prenatal testing of monogenic disorders.

Noa Liscovitch-BrauerRavit MesikaTom RabinowitzHadas VolkovMeitar GradReut Tomashov MatarLina Basel-SalmonOren TadmorAmir BekerNoam Shomron

Published in: Prenatal diagnosis (2024)

Overall, we demonstrate our ability to perform genome-wide NIPS for maternal and homozygous biallelic variants and showcase the utility of our method in a clinical setting.

Keyphrases

genome wide
machine learning
copy number
dna methylation
pregnant women
intellectual disability
artificial intelligence
birth weight
pregnancy outcomes
big data
deep learning
autism spectrum disorder
weight loss