Healthcare systems are under increasing strain due to a myriad of factors, from a steadily
ageing global population to the current COVID-19 pandemic. In a world where we have …

Healthcare data are inherently multimodal, including electronic health records (EHR),
medical images, and multi-omics data. Combining these multimodal data sources …

Background Deep learning has been employed using brain functional connectome data for
evaluating the risk of cognitive deficits in very preterm infants. Although promising, training …

Background Machine learning has been attracting increasing attention for use in healthcare
applications, including neonatal medicine. One application for this tool is in understanding …

Pooling publicly-available MRI data from multiple sites allows to assemble extensive groups
of subjects, increase statistical power, and promote data reuse with machine learning …

Preterm brains commonly exhibit elevated signal intensity in the white matter on T2-
weighted MRI at term-equivalent age. This signal, known as diffuse excessive high signal …

Diabetic macular edema (DME) is a common complication of diabetes that can lead to vision
loss, and anti-vascular endothelial growth factor (anti-VEGF) therapy is the standard of care …

The neurodevelopmental outcomes of preterm infants can be stratified based on the level of
prematurity. We explored brain structural networks in extremely preterm (EP;< 28 weeks of …

Very preterm (VPT) infants (born at less than 32 weeks gestational age) are at high risk for
various adverse neurodevelopmental deficits. Unfortunately, most of these deficits cannot be …

Abstract Background and Objective Very preterm infants are susceptible to
neurodevelopmental impairments, necessitating early detection of prognostic biomarkers for …