Multimodal Inductive Transfer Learning for Detection of Alzheimer s Dementia and its Severity

Alzheimer’s disease is estimated to affect around 50 million people worldwide and is rising rapidly, with a global economic burden of nearly a trillion dollars . We present a novel architecture that leverages acoustic, cognitive, and linguistic features to form a multimodal ensemble system . The system achieves state-of-the-art test accuracy, precision, recall, and F1-score of 83.3% each for AD classification . It uses specialized artificial neural networks with temporal characteristics to detect AD and its severity, which is reflected through Mini-Mental State Exam (MMSE) scores .

Links: PDF - Abstract

Code :

https://github.com/wazeerzulfikar/alzheimers-dementia

Keywords : alzheimer - state - system - multimodal - ad -

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