Deep Learning Application For The Classification Of Alzheimer’s Disease Using 18f-flortaucipir (av-1451) Tau Positron Emission Tomography

This study used Deep Learning (DL) to grade and differentiate the syndromal cognitive stage between Cognitively Unimpaired (CU) and Alzheimer’s Disease (AD), and CU and Mild Cognitive Impairment (MCI). The results of 2D CNN-LSTM and 3D CNN showed high performance in the classification ability of imaging biomarkers. Additionally, demographic and neuropsychological variables were added to the CNN models to integrate multimodal data for disease classification.