Enriching complex networks with word embeddings for detecting mild cognitive impairment from speech transcripts
LB Santos, EA Corrêa Jr, ON Oliveira Jr… - arXiv preprint arXiv …, 2017 - arxiv.org
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 …
features, mainly from parsers, have been used to detect MCI, but this is not suitable for large …
Linguistic-based Mild Cognitive Impairment detection using Informative Loss
This paper presents a deep learning method using Natural Language Processing (NLP)
techniques, to distinguish between Mild Cognitive Impairment (MCI) and Normal Cognitive …
techniques, to distinguish between Mild Cognitive Impairment (MCI) and Normal Cognitive …
[HTML][HTML] Identification of mild cognitive impairment from speech in Swedish using deep sequential neural networks
C Themistocleous, M Eckerström… - Frontiers in neurology, 2018 - frontiersin.org
While people with mild cognitive impairment (MCI) portray noticeably incipient memory
difficulty in remembering events and situations along with problems in decision making …
difficulty in remembering events and situations along with problems in decision making …
Learning linguistic biomarkers for predicting mild cognitive impairment using compound skip-grams
Predicting Mild Cognitive Impairment (MCI) is currently a challenge as existing diagnostic
criteria rely on neuropsychological examinations. Automated Machine Learning (ML) …
criteria rely on neuropsychological examinations. Automated Machine Learning (ML) …
Multi-modal detection of alzheimer's disease from speech and text
Reliable detection of the prodromal stages of Alzheimer's disease (AD) remains difficult
even today because, unlike other neurocognitive impairments, there is no definitive …
even today because, unlike other neurocognitive impairments, there is no definitive …
[PDF][PDF] Detecting mild cognitive impairment by exploiting linguistic information from transcripts
Here we seek to automatically identify Hungarian patients suffering from mild cognitive
impairment (MCI) based on linguistic features collected from their speech transcripts. Our …
impairment (MCI) based on linguistic features collected from their speech transcripts. Our …
[HTML][HTML] A comparison of connected speech tasks for detecting early Alzheimer's disease and mild cognitive impairment using natural language processing and …
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 …
early detection, including of Mild Cognitive Impairment (MCI). Computational analysis of …
Deep-deep neural network language models for predicting mild cognitive impairment
SO Orimaye, JSM Wong… - … in Bioinformatics and …, 2016 - research.monash.edu
Abstract Early diagnosis of Mild Cognitive Impairment (MCI) is currently a challenge.
Currently, MCI is diagnosed using specific clinical diagnostic criteria and …
Currently, MCI is diagnosed using specific clinical diagnostic criteria and …
[HTML][HTML] Screening for mild cognitive impairment using a machine learning classifier and the remote speech biomarker for cognition: Evidence from two clinically …
S Schäfer, E Mallick, L Schwed, A König… - Journal of …, 2023 - content.iospress.com
Background: Modern prodromal Alzheimer's disease (AD) clinical trials might extend
outreach to a general population, causing high screen-out rates and thereby increasing …
outreach to a general population, causing high screen-out rates and thereby increasing …
Identification of mild cognitive impairment among Chinese based on multiple spoken tasks
T Wang, Y Hong, Q Wang, R Su, ML Ng… - Journal of …, 2021 - content.iospress.com
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 …
language for the detection of mild cognitive impairment (MCI). Yet, most of them employed …