Aging is associated with complex biological changes that can be accelerated, slowed, or
even temporarily reversed by biological and non-biological factors. This article focuses on …

The gap between predicted brain age using magnetic resonance imaging (MRI) and
chronological age may serve as a biomarker for early-stage neurodegeneration. However …

Maternal brain adaptations have been found across pregnancy and postpartum, but little is
known about the long-term effects of parity on the maternal brain. Using neuroimaging and …

The deviation between chronological age and age predicted using brain MRI is a putative
marker of overall brain health. Age prediction based on structural MRI data shows high …

Brain-predicted age difference scores are calculated by subtracting chronological age from
'brain'age, which is estimated using neuroimaging data. Positive scores reflect accelerated …

Background Recent genome-wide association studies (GWASs) have revealed the
polygenic nature of psychiatric disorders and discovered a few of single-nucleotide …

Multiple sclerosis (MS) is an inflammatory disorder of the central nervous system. By
combining longitudinal MRI-based brain morphometry and brain age estimation using …

Multimodal imaging enables sensitive measures of the architecture and integrity of the
human brain, but the high-dimensional nature of advanced brain imaging features poses …

Previous structural and functional neuroimaging studies have implicated distributed brain
regions and networks in depression. However, there are no robust imaging biomarkers that …

We ranked third in the Predictive Analytics Competition (PAC) 2019 challenge by achieving
a mean absolute error (MAE) of 3.33 years in predicting age from T1-weighted MRI brain …