Mild Cognitive Impairment (MCI) is a mental disorder difficult to diagnose. Linguistic
features, mainly from parsers, have been used to detect MCI, but this is not suitable for large …

This paper presents a deep learning method using Natural Language Processing (NLP)
techniques, to distinguish between Mild Cognitive Impairment (MCI) and Normal Cognitive …

While people with mild cognitive impairment (MCI) portray noticeably incipient memory
difficulty in remembering events and situations along with problems in decision making …

Predicting Mild Cognitive Impairment (MCI) is currently a challenge as existing diagnostic
criteria rely on neuropsychological examinations. Automated Machine Learning (ML) …

Reliable detection of the prodromal stages of Alzheimer's disease (AD) remains difficult
even today because, unlike other neurocognitive impairments, there is no definitive …

Here we seek to automatically identify Hungarian patients suffering from mild cognitive
impairment (MCI) based on linguistic features collected from their speech transcripts. Our …

Alzheimer's disease (AD) has a long pre-clinical period, and so there is a crucial need for
early detection, including of Mild Cognitive Impairment (MCI). Computational analysis of …

Abstract Early diagnosis of Mild Cognitive Impairment (MCI) is currently a challenge.
Currently, MCI is diagnosed using specific clinical diagnostic criteria and …

Background: Modern prodromal Alzheimer's disease (AD) clinical trials might extend
outreach to a general population, causing high screen-out rates and thereby increasing …

Background: Previous studies explored the use of noninvasive biomarkers of speech and
language for the detection of mild cognitive impairment (MCI). Yet, most of them employed …