Systems and methods are provided for color-coded visualization to aid in diagnosis and prognosis of Alzheimer's disease (AD). The color-coded visualization mechanism can be driven by an integrated machine learning (ML) model, which can take as its inputs neuroimaging (e.g., magnetic resonance imaging (MRI), positron emission tomography (PET)) data, neuropsychological test scores, the cerebrospinal fluid (CSF) biomarker, and/or risk factors. With these inputs, the ML model can generate a color-coded visualization of the disease state.