The prediction of patients who are at higher risk converting to Mild Cognitive Impairment (MCI) is critical for effective intervention and patient selection in clinical trials. We are developing novel deep learning models using surrogate biomarkers and transfer learning approaches to build a model that can accurately predict the risk score of such patients.