Structural MRI is routinely acquired in clinical practice, yet quantitative morphometry has had limited impact on clinical decision-making. Overlapping symptoms, trajectories and comorbidities remain difficult to interpret within disease-specific frameworks, leaving it unclear how individual patients relate to the broa...
C. Dalby, A. Dibble, S. Benini et al.· medRxiv· 1 citation
An explainable deep learning framework for identifying distributed, individualized neurodegeneration signatures of NPS burden across the AD continuum is introduced.
B. Yaghooti, S. Ishrat, H. Le et al.· medRxiv· 0 citations
Introduction: Polygenic risk scores (PRS) may improve Alzheimer's disease (AD) risk prediction before symptom onset, yet choosing an appropriate model can be challenging. Methods: Using the standardized GenoPred pipeline, 1,752 PRS models (9 algorithms; 584 configurations; 3 genome-wide association studies) were evalua...
Elizabeth L. Ward, Peter T. Nelson, Y. Katsumata et al.· medRxiv· 0 citations
These findings, replicated in four diverse and independent datasets, support imaging-based subtyping as a scalable and clinically translatable approach for capturing heterogeneity in AD pathophysiology and associated cognitive trajectories.
A. Metz, Cassandra Polizzi, R. Moqadam et al.· medRxiv· 0 citations
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