MAPT and Alzheimer disease: Deep learning models trained on structural MRI to predict cerebrospinal fluid‐based amyloid and tau concentrations can generate latent representations (MRI‐derived CSF proxy/surrogate markers) that can be subsequently transferred for Alzheimer's disease detection and risk prediction, bypassing noninvasive testing and enabling regional distribution mapping via intuitive feature attribution approaches.