Predicting Alzheimer’s disease progression in healthy and MCI subjects using multi‐modal deep learning approach

Alzheimer's disease (AD) is a complex disorder influenced by many factors, but it is unclear how each factor contributes to disease progression. An in‐depth examination of these factors may yield an accurate estimate of time‐to‐conversion to AD for patients at various disease stages. Recent advances in deep learning have enabled researchers to predict patient’s disease onset time by exploring the influencing factors in AD progression.