3 papers
cs.CV2026
Interpretable machine learning predicts Parkinson's disease severity using motion-corrected QSM MRI and multiband multiecho fMRI features
Aixa X. Andrade
Introduction: Objective neuroimaging biomarkers may improve Parkinson's disease motor assessment by capturing brain variation not directly observable from clinical examination. We…
cs.LG2024
scMEDAL for the interpretable analysis of single-cell transcriptomics data with batch effect visualization using a deep mixed effects autoencoder
Aixa X. Andrade, Son Nguyen, Austin Marckx +1
Single-cell RNA sequencing enables high-resolution analysis of cellular heterogeneity, yet disentangling biological signal from batch effects remains a major challenge. Existing ba…
q-bio.NC2022
Longitudinal Prognosis of Parkinsons Outcomes using Causal Connectivity
Cooper J. Mellema, Kevin P. Nguyen, Alex Treacher +2
Parkinsons disease (PD) is a movement disorder and the second most common neurodengerative disease but despite its relative abundance, there are no clinically accepted neuroimaging…