K-operator as a predictor for Alzheimer-Perusini’s disease

Progressive memory loss occurring in age-related neurological diseases contributes to the disgregation of the individual, with serious personal and social consequences. We model the brain network damage provoked by a neurological disease through a physics-inspired mathematical operator, K. Acting on a diseased brain, K provides the disease time evolution. Focusing on Alzheimer-Perusini's disease (AD), we approximate the K-operator considering selected patients of the ADNI 2 dataset. We also propose K as a predictor for the disease progress over time and give its preliminary evaluation in the AD progression from the cognitive normal (CN) stage to AD through intermediate mild cognitive impairment (MCI) stages.