Mingzhao Tong

This paper develops a continuous amyloid staging score from regional amyloid PET to improve early Alzheimer's disease staging and cognitive risk stratification.

This paper models Alzheimer's disease progression as a deviation from aging using longitudinal amyloid PET data and a self-supervised trajectory-learning framework, revealing distinct trajectories in early-stage aging and AD.

This study introduces SLOPE, a method to model amyloid progression in Alzheimer's disease on a continuous trajectory, showing improved sensitivity to early changes compared to global measures.