[HTML][HTML] Speech and language processing with deep learning for dementia diagnosis: A systematic review

M Shi, G Cheung, SR Shahamiri - Psychiatry Research, 2023 - Elsevier
Dementia is a progressive neurodegenerative disease that burdens the person living with
the disease, their families, and medical and social services. Timely diagnosis of dementia …

Noninvasive automatic detection of Alzheimer's disease from spontaneous speech: a review

X Qi, Q Zhou, J Dong, W Bao - Frontiers in Aging Neuroscience, 2023 - frontiersin.org
Alzheimer's disease (AD) is considered as one of the leading causes of death among
people over the age of 70 that is characterized by memory degradation and language …

Multimodal fusion for alzheimer's disease recognition

Y Ying, T Yang, H Zhou - Applied Intelligence, 2023 - Springer
Alzheimer's disease (AD) is the most prevalent form of progressive degenerative dementia,
which has a great impact on social economics throughout the world. In the vast majority of …

[PDF][PDF] Alzheimer's Detection from English to Spanish Using Acoustic and Linguistic Embeddings.

PA Pérez-Toro, P Klumpp, A Hernandez, T Arias… - Interspeech, 2022 - isca-archive.org
Cross-lingual approaches are growing in popularity in the machine learning domain, where
large amounts of data are required to obtain better generalizations. Moreover, one of the …

A mobile application using automatic speech analysis for classifying Alzheimer's disease and mild cognitive impairment

Y Yamada, K Shinkawa, M Nemoto, K Nemoto… - Computer Speech & …, 2023 - Elsevier
Speech and language disturbances have been observed from the early stages of
Alzheimer's disease (AD), including mild cognitive impairment (MCI), and speech analysis …

Depression assessment in people with Parkinson's disease: The combination of acoustic features and natural language processing

PA Pérez-Toro, T Arias-Vergara, P Klumpp… - Speech …, 2022 - Elsevier
Parkinson's disease produces motor impairments such as bradykinesia, rigidity, and
different speech impairments, as same as non-motor symptoms like cognitive decline and …

Efficient pause extraction and encode strategy for alzheimer's disease detection using only acoustic features from spontaneous speech

J Liu, F Fu, L Li, J Yu, D Zhong, S Zhu, Y Zhou, B Liu… - Brain Sciences, 2023 - mdpi.com
Clinical studies have shown that speech pauses can reflect the cognitive function
differences between Alzheimer's Disease (AD) and non-AD patients, while the value of …

Interpreting acoustic features for the assessment of Alzheimer's disease using ForestNet

PA Pérez-Toro, D Rodríguez-Salas, T Arias-Vergara… - Smart Health, 2022 - Elsevier
Nowadays, interpretable machine learning models are one of the most critical topics in the
medical domain. The lack of interpretation leads to blind and unreliable models for …

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 …

Going beyond the cookie theft picture test: Detecting cognitive impairments using acoustic features

F Braun, A Erzigkeit, H Lehfeld, T Hillemacher… - … Conference on Text …, 2022 - Springer
Standardized tests play a crucial role in the detection of cognitive impairment. Previous work
demonstrated that automatic detection of cognitive impairment is possible using audio data …