Advanced Analytics, AI, and Computational Phenotyping

What this project does
Applies advanced analytics, AI, and machine learning to identify patterns across complex ADRD data.

Why it matters clinically
Computational approaches help uncover disease subtypes, progression patterns, and biologically meaningful signals that are not visible through single measures.

Key activities
-Develop and refine AI/machine learning models
-Integrate multimodal data (clinical, imaging, biomarkers, genomics)
-Support computational phenotyping and predictive modeling
-Collaborate closely with Clinical, Biomarker, Imaging, and Neuropathology Cores

What will be delivered
-Predictive and stratification models
-Integrated analytic pipelines for multimodal ADRD research

Who this helps
-Investigators studying disease heterogeneity
-Researchers developing precision medicine approaches