Jane W. Newburger

A Large-Scale Deep Normative Modeling of Primary Sulcal Patterns Reveals Deviations in a Spectrum of Disorders

This paper introduces a deep learning model to detect sulcal pattern deviations in neurological disorders using a large cohort of typically developing individuals.

Scoring gene importance by interpreting single-cell foundation models

The paper introduces SIGnature, a framework for scoring gene importance using attributions from scRNA-seq foundation models, and demonstrates its utility in identifying novel associations of the MS1 signature with hyperinflammatory conditions.

Genome Sequencing is Critical for Forecasting Outcomes Following Congenital Cardiac Surgery

This study uses AI to show that genome sequencing can predict adverse outcomes after congenital heart defect surgery by identifying damaging genotypes in specific genes.

Genetic, demographic and clinical variables act synergistically to impact neurodevelopmental outcomes in children with single ventricle heart disease

The paper examines how genetic, demographic, and clinical factors interact to influence neurodevelopmental outcomes in children with single ventricle heart disease.

Early post-zygotic mutations contribute to congenital heart disease

The paper identifies mosaic mutations in blood and cardiac tissue from CHD patients, finding 1% of cases have detectable mosaic variants that may contribute to congenital heart disease.