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J. Kornak

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Open access Sep 2026

Smartphone Passive Digital Phenotyping in Frontotemporal Lobar Degeneration

Introduction: Frontotemporal lobar degeneration (FTLD) is a devastating disease that commonly results in early onset dementia, yet its rarity and heterogeneity limit large-scale research and clinical trials. Remote monitoring via low-burden digital health tools may overcome these barriers. We evaluated clinical utility...

E. Paolillo, Sreya Dhanam, J. Taylor et al. · 0 citations
Open access Sep 2026

CSF proteomics and machine learning reveal distinct stages across the Alzheimer’s disease continuum

These findings uncover protein signatures that reflect underlying AD biology and provide a foundation for stage-specific biomarkers and therapeutic targeting, with important implications for patient stratification and personalized intervention strategies.

Saima Rathore, E. Dammer, Anantharaman Shantaraman et al. · 0 citations
#machine learning Open access Dec 2024

Enhancing brain age estimation with structural MRI and synthesized cerebral blood volume maps

Abstract Brain age gap estimation (BrainAGE) is a promising imaging-derived biomarker of neurobiological ageing and disease risk, yet current approaches rely predominantly on T1-weighted structural MRI, overlooking functional vascular changes that may precede tissue damage and cognitive decline. Deep learning-derived c...

Jordan Jomsky, Zongyu Li, K. Igwe et al. · 1 citation
#protein folding Open access Aug 2026

Cerebrospinal fluid YWHAG:NPTX2 ratio predicts clinical severity and future phenoconversion in frontotemporal lobar degeneration

Frontotemporal lobar degeneration (FTLD) is a common cause of early-onset dementias marked by progressive declines in behavior, cognition, and/or movement. FTLD neuropathologies, including TDP-43 proteinopathies and primary tauopathies, do not have reliable fluid biomarkers for in-vivo diagnosis nor biomarkers that dir...

H. Oh, J. Downer, Connor D. Dietz et al. · 0 citations

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