Figure 3.

Flowchart of the proposed method. The MRI data and clinical scores are extracted for longitudinal feature selection, with smoothness regularization (i.e., feature-feature, subject-subject, and clinical score-clinical score relation guided regularizers) and a group sparsity induced regularization. After longitudinal feature selection, the feature dimension is reduced, and the selected features are employed to build ADAS-Cog and MMSE regression models for prediction.