Author

Emanuel A. Azcona

Northwestern UniversityORCID 0000-0002-1896-4823Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Approach:deep learning· 2 Organism:human· 2 Assay:imaging· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Approach:graph neural network· 1

Frequent Co-Authors

Aggelos K. KatsaggelosiD· 2 shared Pierre BessoniD· 2 shared S. Kathleen BandtiD· 2 shared Todd B. ParrishiD· 2 shared Yunan WuiD· 2 shared Ajay S. KuraniiD· 1 shared Alzheimer’s Disease Neuroimaging Initiative· 1 shared Hans C Breiter· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 26 mutual co-author links

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2 shared papersNeuroscience

Aggelos K. KatsaggelosORCID

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2 papers

Recent·Most cited

NeurosciencebioRxivPreprintApr 15, 2021

Analyzing Brain Morphology in Alzheimer's Disease Using Discriminative and Generative Spiral Networks

Emanuel A. Azcona, Pierre Besson, Yunan Wu…·Alzheimer’s Disease Neuroimaging Initiative

This paper introduces geometric deep learning frameworks for analyzing brain morphology in Alzheimer's disease, showing improved classification and morphological insights compared to prior methods.

3 citations

humanimaging

𝕏 PostBluesky

NeurosciencebioRxivPreprintOct 14, 2020

Novel age-dependent cortico-subcortical morphologic interactions predict fluid intelligence: A multi-cohort geometric deep learning study.

Yunan Wu, Pierre Besson, Emanuel A. Azcona…·Aggelos K. Katsaggelos

This study uses geometric deep learning to predict fluid intelligence from brain morphology across two cohorts, finding that amygdala, hippocampus, and specific cortical regions are key predictors.

5 citations

humanimaging

𝕏 PostBluesky