Linguistic markers predict onset of Alzheimer's disease
Background The aim of this study is to use classification methods to predict future onset of
Alzheimer's disease in cognitively normal subjects through automated linguistic analysis …
Alzheimer's disease in cognitively normal subjects through automated linguistic analysis …
Temporal integration of text transcripts and acoustic features for Alzheimer's diagnosis based on spontaneous speech
Background: Advances in machine learning (ML) technology have opened new avenues for
detection and monitoring of cognitive decline. In this study, a multimodal approach to …
detection and monitoring of cognitive decline. In this study, a multimodal approach to …
[HTML][HTML] Discriminating speech traits of Alzheimer's disease assessed through a corpus of reading task for Spanish language
O Ivanova, JJG Meilán, F Martínez-Sánchez… - Computer Speech & …, 2022 - Elsevier
It is estimated that between 50% and 75% of all cases of dementia are due to Alzheimer's
disease (AD), the most common neurodegenerative disease among World population …
disease (AD), the most common neurodegenerative disease among World population …
ADscreen: A speech processing-based screening system for automatic identification of patients with Alzheimer's disease and related dementia
Alzheimer's disease and related dementias (ADRD) present a looming public health crisis,
affecting roughly 5 million people and 11% of older adults in the United States. Despite …
affecting roughly 5 million people and 11% of older adults in the United States. Despite …
Classification of Alzheimer's disease with deep learning on eye-tracking data
Existing research has shown the potential of classifying Alzheimer's Disease (AD) from eye-
tracking (ET) data with classifiers that rely on task-specific engineered features. In this paper …
tracking (ET) data with classifiers that rely on task-specific engineered features. In this paper …
Unveiling the sound of the cognitive status: Machine Learning-based speech analysis in the Alzheimer's disease spectrum
Background Advancement in screening tools accessible to the general population for the
early detection of Alzheimer's disease (AD) and prediction of its progression is essential for …
early detection of Alzheimer's disease (AD) and prediction of its progression is essential for …
Longitudinal speech biomarkers for automated alzheimer's detection
J Laguarta, B Subirana - frontiers in Computer Science, 2021 - frontiersin.org
We introduce a novel audio processing architecture, the Open Voice Brain Model (OVBM),
improving detection accuracy for Alzheimer's (AD) longitudinal discrimination from …
improving detection accuracy for Alzheimer's (AD) longitudinal discrimination from …
Classification of Alzheimer's using Deep-learning Methods on Webcam-based Gaze Data
There has been increasing interest in non-invasive predictors of Alzheimer's disease (AD)
as an initial screen for this condition. Previously, successful attempts leveraged eye-tracking …
as an initial screen for this condition. Previously, successful attempts leveraged eye-tracking …
The Optimization of a Natural Language Processing Approach for the Automatic Detection of Alzheimer's Disease Using GPT Embeddings
BS Runde, A Alapati, NG Bazan - Brain Sciences, 2024 - mdpi.com
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 …
disease (AD) is essential for its early prevention and mitigation. We optimize the detection of …
Classification of Alzheimer's disease leveraging multi-task machine learning analysis of speech and eye-movement data
Alzheimer's disease (AD) is a progressive neurodegenerative condition that results in
impaired performance in multiple cognitive domains. Preclinical changes in eye movements …
impaired performance in multiple cognitive domains. Preclinical changes in eye movements …