Hierarchical Transformer for Early Detection of Alzheimer’s Disease

Alzheimer's disease is an irreversible disease that severely affect the brain functions and life quality of the patients. For now, there is no effective cure for the disease. Therefore this unfortunate fact makes the early detection of Alzheimer's disease vital. The early stage of the Alzheimer's disease, Mild Cognitive Impairment (MCI), normally involve loss in memory, language ability, and object recognition ability. In this paper, we present a new dataset that includes the transcribed audio of MCI patients and healthy subject. We also present a hierarchical transformer-based model and the corresponding analysis for the MCI/health classification task on our dataset.