AI-driven fusion of neurological work-up for assessment of biological Alzheimer's disease.

ABSTRACT: Alzheimer's disease (AD) diagnosis hinges on detecting amyloid beta (Aβ) plaques and neurofibrillary tau (τ) tangles. While amyloid PET imaging is now clinically approved, tau PET remains largely restricted to research settings. These imaging techniques, though valuable, are expensive and often difficult to access, limiting their widespread use in routine clinical practice. Here, we introduce a computational framework that leverages multimodal data from seven distinct cohorts comprising 12, 185 participants to estimate individual PET profiles, both global and regional, using more accessible data modalities, such as demographics, medical history, medication use, fluid measurements, functional and neuropsychological assessments, and structural MRIs. Our approach achieved an are

SUBMITTER: Jasodanand VH 

PROVIDER: S-EPMC11957082 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature