Background: People with Alzheimer's disease (AD) often demonstrate difficulties in
discourse production. Referential communication tasks (RCTs) are used to examine a …

Introduction: Research related to the automatic detection of Alzheimer's disease (AD) is
important, given the high prevalence of AD and the high cost of traditional diagnostic …

Background: Although memory impairment is the main symptom of Alzheimer's disease
(AD), language impairment can be an important marker. Relatively few studies of language …

Background: Recently, many studies have been carried out to detect Alzheimer's disease
(AD) from continuous speech by linguistic analysis and modeling. However, few of them …

The development of noninvasive and cost-effective methods of detecting Alzheimer's
disease (AD) is essential for its early prevention and mitigation. We optimize the detection of …

Picture description tasks are used for the detection of cognitive decline associated with
Alzheimer's disease (AD). Recent years have seen work on automatic AD detection in …

Clinical literature provides convincing evidence that language deficits in Alzheimer's
disease (AD) allow for distinguishing patients with dementia from healthy subjects …

Alzheimer's Disease (AD) is a form of dementia that affects the memory, cognition, and motor
skills of patients. Extensive research has been done to develop accessible, cost-effective …

The need for inexpensive, safe, accurate and non-invasive biomarkers for Alzheimer's
disease (AD) has motivated much current research (Mandell and Green, 2011). While …

Natural language processing (NLP) has exhibited potential in detecting Alzheimer's disease
(AD) and related dementias, particularly due to the impact of AD on spontaneous speech …