Passive Digital Markers for Alzheimer’s Disease and Related Dementia Predict Mild Cognitive Impairment

Alzheimer’s Disease and Related Dementia (ADRD) typically progresses through three clinical stages: Normal Cognition (NC), Mild Cognitive Impairment (MCI), and ADRD. Early detection of MCI is critical for identifying individuals at high risk for ADRD for proper management and early interventions to prevent progression to ADRD. Recently, Boustani et al. identified a passive signature in unstructured Electronic Medical Records (EMR) data for early detection of ADRD. Our objective is to test whether machine learning models trained using ADRD Passive Digital Markers (PDMs) can accurately predict MCI 3 years in advance.