TPE: finding the turning point in disease progression
Disease trajectories are not lines. They bend, and the bend is where the clinical meaning hides.
Alzheimer's Association International Conference (AAIC) 2026
I will remotely attend AAIC 2026 in London to present recent work in neuroimaging and machine learning for Alzheimer's disease.
PET Tracer Classification and the Tau Therapeutic Window
A podium talk on a 2.5D deep learning classifier for PET tracer identification, and a poster introducing the tau therapeutic window as an eligibility criterion for anti-amyloid …
PET Tracer Classification
Deep learning identifies PET radiotracers directly from brain scans to improve quality control in multi-site studies.
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1 min read
MSA and Parkinson's Disease Imaging Heterogeneity
MRI-based machine learning distinguishes multiple system atrophy subtypes from Parkinson's disease and quantifies disease heterogeneity.
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1 min read
THETA: Tau PET Quantification in Alzheimer's Disease
THETA measures the spatial heterogeneity of tau PET signal in Alzheimer's disease using machine learning.
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1 min read