Multimodal attention-based deep learning for Alzheimer's disease diagnosis

Michal Golovanevsky, Carsten Eickhoff, Ritambhara Singh

Abstract: Alzheimer’s disease (AD) is the most common neurodegenerative disorder with one of the most complex pathogeneses, making effective and clinically actionable decision support difficult. The objective of this study was to develop a novel multimodal deep learning framework to aid medical professionals in AD diagnosis.