Research

Med AI Lab conducts cutting-edge research at the intersection of artificial intelligence, neuroimaging, and biomarker science to better understand and diagnose neurodegenerative diseases—primarily Alzheimer’s and Parkinson’s. Their work spans several core areas: developing non-invasive blood-based and imaging biomarkers, using AI to predict disease progression, studying sex-related differences in biomarker effectiveness, and identifying the role of vascular and glymphatic systems in early disease mechanisms. The lab also investigates overlapping pathologies, such as Lewy Body disease, and enhances diagnostic tools using advanced PET/MRI techniques and machine learning models. Overall, the lab’s interdisciplinary research aims to improve early detection, personalize clinical trials, and accelerate discoveries that lead to better patient outcomes in brain health.

Explore the research topics below to learn more about each project in detail.

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MED AI Lab
Topics
Cognitive Biomarkers
Alzheimer's
Parkinson's
PET Biomarkers

Lewy Body pathology is detected in individuals spanning the Alzheimer's Disease spectrum

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Neurodegenerative disorders, such as Alzheimer's disease (AD) and Lewy Body disease, often present increasing co-pathologies with time and disease progression. In AD patients, amyloid plaques, tau tangles, and alpha-synuclein aggregates (Lewy bodies, LBs) are commonly found in brain tissue at autopsy, suggesting overlap - or "cross-talk' - between and among these pathogenic entities that ultimately lead to synaptic death and cognitive impairment. Dr Tosun and colleagues recently tested cerebrospinal fluid (CSF) samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort and found that 22% contained pathogenic forms of LBs. The prevalence of LBs was found to increase with disease stage and age, and was associated with greater cognitive decline and earlier symptom onset. LB prevalence and its associations with AD biomarkers have been published in two separate articles this year, one with cross-sectional data and the other with longitudinal data from the ADNI.
MED AI Lab
Topics
AI
MRI
Parkinson's

Medical Imaging Informatics and AI wins 2016 PPMI Data Challenge

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Michael J Fox Foundation named the winners of the 2016 Parkinson's Progression Markers Initiative Data Challenge (PPMI).