Linguistic biomarkers as a diagnostic and prognostic tool for identifying Alzheimer’s Disease

Background: Alzheimer's disease (AD), a major public health challenge, is the third leading cause of death among older adults in the United States and exacts significant economic and societal costs. Despite extensive research and development efforts yielding a deeper understanding of its pathophysiology, effective treatments for AD remain elusive. Therapeutic approaches to date have failed to halt or meaningfully slow the disease's progression, highlighting the urgent need for early diagnosis and intervention. Traditional diagnostic methods, such as protein assays, genetic testing, and neuroimaging, are often costly, invasive, and not fully predictive of associated cognitive decline. This necessitates the exploration of more accessible and earlier diagnostic tools.