Hammond et al. used an advanced statistical learning machine learning method, random forest, on data provided by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to measure the ability of beta-amyloid measured by positron emission tomography (Aβ-PET), phosphorylated tau measured in the cerebral spinal fluid (CSF-pTau), fluorodeoxyglucose measured by positron emission tomography (FDG-PET) and structural imaging measured by magnetic resonance imaging (MRI) to classify AD diagnosis. This evidence concerns the gene MAPT and early-onset autosomal dominant Alzheimer disease.