Retinal Deposits of TDP‐43 and Amyloid Beta and Associated Neurodegenerative Diseases are Accurately Classified using Measured Interactions with Polarized Light in Machine Learning Algorithms

Machine learning, using the averages and standard deviations of polarized light properties in RF or images showing the distribution of these properties across the deposits (CNN) can differentiate retinal deposits associated with Alzheimer's disease from those associated with ALS and FTLD, with a relatively high accuracy. This first differential diagnostic of Alzheimer's disease from TDP-43 related diseases, is early, non-invasive and inexpensive and would reach underserved populations.