Chatbot May Detect Early Dementia in Time for Intervention

Medical Xpress reports that a study in IEEE Access found that the early detection of Alzheimer's dementia (AD) can stabilize or even curtail neural deterioration. Queensland University of Technology (QUT) researchers crafted automatic machine learning models using language features to identify multiple stages of dementia, including Mild Cognitive Impairment (MCI), possible AD (PoAD), and probable AD. "Early stages of dementia can be efficiently diagnosed through linguistic patterns and deficits using machine learning models," explained QUT's Ahmed Alkenani. "Early, accurate diagnosis is important to enable clinicians to intervene in time to delay or prevent Alzheimer's dementia." The study examined language samples from DementiaBank, a database of language samples from people in various stages of cognitive impairment and dementia. "We studied 236 language samples from people diagnosed with probable AD, 43 samples from people with MCI, 21 samples belonging to people with possible AD, and 243 from healthy people," said Alkenani. "We found people with dementia leaned towards using fewer nouns but more verbs, pronouns, and adjectives as dementia progressed compared to healthy adults." Alkenani added that the ultimate goal "is to develop a conversational agent or chatbot that could be used remotely to facilitate the initial diagnosis of early stage dementia as an attempt to replace traditional screening tests."