Jianfeng Wu

This paper introduces a federated model to integrate sMRI, GWAS, and transcriptomics data in Alzheimer's disease to identify genetic and transcriptomic influences on brain imaging measures.

This paper introduces FMFS, a framework for selecting hippocampal morphometry features linked to Aβ/tau pathology, showing it outperforms existing methods and identifies key subregions for biomarker development.

This paper develops a method to predict brain amyloid burden using MRI-based morphometry statistics and sparse coding, achieving high accuracy in ADNI and OASIS cohorts.