A review of machine learning and deep learning approaches on mental health diagnosis

NK Iyortsuun, SH Kim, M Jhon, HJ Yang, S Pant - Healthcare, 2023 - mdpi.com
Combating mental illnesses such as depression and anxiety has become a global concern.
As a result of the necessity for finding effective ways to battle these problems, machine …

Artificial intelligence, speech, and language processing approaches to monitoring Alzheimer's disease: a systematic review

S De la Fuente Garcia, CW Ritchie… - Journal of Alzheimer's …, 2020 - content.iospress.com
Background: Language is a valuable source of clinical information in Alzheimer's disease,
as it declines concurrently with neurodegeneration. Consequently, speech and language …

Predicting dementia from spontaneous speech using large language models

F Agbavor, H Liang - PLOS digital health, 2022 - journals.plos.org
Language impairment is an important biomarker of neurodegenerative disorders such as
Alzheimer's disease (AD). Artificial intelligence (AI), particularly natural language processing …

Alzheimer's dementia recognition through spontaneous speech

S Luz, F Haider, S de la Fuente Garcia… - Frontiers in computer …, 2021 - frontiersin.org
The need for inexpensive, safe, accurate and non-invasive biomarkers for Alzheimer's
disease (AD) has motivated much current research (Mandell and Green, 2011). While …

Detecting cognitive decline using speech only: The adresso challenge

S Luz, F Haider, S de la Fuente, D Fromm… - arXiv preprint arXiv …, 2021 - arxiv.org
Building on the success of the ADReSS Challenge at Interspeech 2020, which attracted the
participation of 34 teams from across the world, the ADReSSo Challenge targets three …

Linguistic features identify Alzheimer's disease in narrative speech

KC Fraser, JA Meltzer… - Journal of Alzheimer's …, 2015 - journals.sagepub.com
Background: Although memory impairment is the main symptom of Alzheimer's disease
(AD), language impairment can be an important marker. Relatively few studies of language …

To BERT or not to BERT: comparing speech and language-based approaches for Alzheimer's disease detection

A Balagopalan, B Eyre, F Rudzicz… - arXiv preprint arXiv …, 2020 - arxiv.org
Research related to automatically detecting Alzheimer's disease (AD) is important, given the
high prevalence of AD and the high cost of traditional methods. Since AD significantly affects …

An assessment of paralinguistic acoustic features for detection of Alzheimer's dementia in spontaneous speech

F Haider, S De La Fuente, S Luz - IEEE Journal of Selected …, 2019 - ieeexplore.ieee.org
Speech analysis could provide an indicator of Alzheimer's disease and help develop clinical
tools for automatically detecting and monitoring disease progression. While previous studies …

D-vlog: Multimodal vlog dataset for depression detection

J Yoon, C Kang, S Kim, J Han - Proceedings of the AAAI Conference on …, 2022 - ojs.aaai.org
Detecting depression based on non-verbal behaviors has received great attention.
However, most prior work on detecting depression mainly focused on detecting depressed …

Artificial intelligence for Alzheimer's disease: promise or challenge?

C Fabrizio, A Termine, C Caltagirone, G Sancesario - Diagnostics, 2021 - mdpi.com
Decades of experimental and clinical research have contributed to unraveling many
mechanisms in the pathogenesis of Alzheimer's disease (AD), but the puzzle is still …