Before revision:  A pre-trained age predictor , which estimates the apparent age of a brain image, is used to assess age accuracy. In addition, we show that we can train the model on Cam-CAN data and evaluate on the longitudinal data from ADNI, indicating the generalisation power of our approach.
After revision:  A pre-trained age predictor . We show that, despite the use of cross-sectional data, our model learns patterns of gray matter atrophy in the middle temporal gyrus in patients with AD. To demonstrate generalisation ability, we train on the longitudinal data from ADNI, indicating the generalisation power of our approach.