Deep learning-based speech analysis for Alzheimer's disease detection: a literature review

Q Yang, X Li, X Ding, F Xu, Z Ling - Alzheimer's Research & Therapy, 2022 - Springer
Background Alzheimer's disease has become one of the most common neurodegenerative
diseases worldwide, which seriously affects the health of the elderly. Early detection and …

[HTML][HTML] Dementia detection from speech using machine learning and deep learning architectures

MR Kumar, S Vekkot, S Lalitha, D Gupta, VJ Govindraj… - Sensors, 2022 - mdpi.com
Dementia affects the patient's memory and leads to language impairment. Research has
demonstrated that speech and language deterioration is often a clear indication of dementia …

[HTML][HTML] Automatic depression detection using smartphone-based text-dependent speech signals: deep convolutional neural network approach

AY Kim, EH Jang, SH Lee, KY Choi, JG Park… - Journal of medical …, 2023 - jmir.org
Background Automatic diagnosis of depression based on speech can complement mental
health treatment methods in the future. Previous studies have reported that acoustic …

Language impairment in Alzheimer's disease—robust and explainable evidence for ad-related deterioration of spontaneous speech through multilingual machine …

H Lindsay, J Tröger, A König - Frontiers in aging neuroscience, 2021 - frontiersin.org
Alzheimer's disease (AD) is a pervasive neurodegenerative disease that affects millions
worldwide and is most prominently associated with broad cognitive decline, including …

ADscreen: A speech processing-based screening system for automatic identification of patients with Alzheimer's disease and related dementia

M Zolnoori, A Zolnour, M Topaz - Artificial intelligence in medicine, 2023 - Elsevier
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 …

MSCCov19Net: multi-branch deep learning model for COVID-19 detection from cough sounds

S Ulukaya, AA Sarıca, O Erdem, A Karaali - Medical & Biological …, 2023 - Springer
Coronavirus has an impact on millions of lives and has been added to the important
pandemics that continue to affect with its variants. Since it is transmitted through the …

Multimodal deep learning models for detecting dementia from speech and transcripts

L Ilias, D Askounis - Frontiers in aging neuroscience, 2022 - frontiersin.org
Alzheimer's dementia (AD) entails negative psychological, social, and economic
consequences not only for the patients but also for their families, relatives, and society in …

Unveiling the sound of the cognitive status: Machine Learning-based speech analysis in the Alzheimer's disease spectrum

F García-Gutiérrez, M Alegret, M Marquié… - Alzheimer's Research & …, 2024 - Springer
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 …

Speech based detection of Alzheimer's disease: a survey of AI techniques, datasets and challenges

K Ding, M Chetty, A Noori Hoshyar… - Artificial Intelligence …, 2024 - Springer
Alzheimer's disease (AD) is a growing global concern, exacerbated by an aging population
and the high costs associated with traditional detection methods. Recent research has …

Comparison of AI with and without hand-crafted features to classify Alzheimer's disease in different languages

TM Kim, J Son, JW Chun, Y Lee, DJ Kim, IY Choi… - Computers in Biology …, 2024 - Elsevier
Abstract Background Detecting and analyzing Alzheimer's disease (AD) in its early stages is
a crucial and significant challenge. Speech data from AD patients can aid in diagnosing AD …