Giancarlo Natalucci

This paper uses graph convolutional networks to classify neonatal brain connectomes by etiology at voxel-level granularity, achieving higher classification performance than atlas-based methods and a multilayer perceptron baseline.

The paper identifies genetic pathways and variants associated with sepsis susceptibility in children through genomic analysis of a paediatric cohort.

This paper identifies a genetic locus associated with sepsis susceptibility in children using a genome-wide association study of a national cohort.

This study examines structural brain connectome differences in newborns at risk for cognitive developmental delay across multiple etiologies, finding altered network topology features associated with poorer cognitive outcomes.

This study uses deformation-based morphometry on longitudinal MRI scans to analyze changes in brain asymmetry from fetal to neonatal stages, identifying key regions of asymmetry and developmental shifts.

The paper links thalamocortical connectivity in preterm infants to mental developmental outcomes using diffusion MRI.

This study examines the link between early amplitude-integrated EEG (aEEG) and neurodevelopmental outcomes in preterm infants, finding that aEEG measures are not predictive after adjusting for confounders.