Machine learning for dementia prediction: a systematic review and future research directions

A Javeed, AL Dallora, JS Berglund, A Ali, L Ali… - Journal of medical …, 2023 - Springer
Abstract Nowadays, Artificial Intelligence (AI) and machine learning (ML) have successfully
provided automated solutions to numerous real-world problems. Healthcare is one of the …

Speaker identification through artificial intelligence techniques: A comprehensive review and research challenges

R Jahangir, YW Teh, HF Nweke, G Mujtaba… - Expert Systems with …, 2021 - Elsevier
Speech is a powerful medium of communication that always convey rich and useful
information, such as gender, accent, and other unique characteristics of a speaker. These …

An automatic Alzheimer's disease classifier based on spontaneous spoken English

F Bertini, D Allevi, G Lutero, L Calzà… - Computer Speech & …, 2022 - Elsevier
Abstract According to the World Health Organization, the number of people suffering from
dementia worldwide will grow to 150 million by mid-century, and Alzheimer's disease is the …

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 …

Automatic speech classifier for mild cognitive impairment and early dementia

F Bertini, D Allevi, G Lutero, D Montesi… - ACM Transactions on …, 2021 - dl.acm.org
The World Health Organization estimates that 50 million people are currently living with
dementia worldwide and this figure will almost triple by 2050. Current pharmacological …

Explainable identification of dementia from transcripts using transformer networks

L Ilias, D Askounis - IEEE Journal of Biomedical and Health …, 2022 - ieeexplore.ieee.org
Alzheimer's disease (AD) is the main cause of dementia which is accompanied by loss of
memory and may lead to severe consequences in peoples' everyday life if not diagnosed on …

Advances in multimodal behavioral analytics for early dementia diagnosis: A review

C Palliya Guruge, S Oviatt, P Delir Haghighi… - Proceedings of the …, 2021 - dl.acm.org
Clinical diagnosis of dementia is typically delayed and limited in accuracy, despite
assessing cognitive impairments through neurological exams, brain imaging, and functional …

Gpt-d: Inducing dementia-related linguistic anomalies by deliberate degradation of artificial neural language models

C Li, D Knopman, W Xu, T Cohen… - arXiv preprint arXiv …, 2022 - arxiv.org
Deep learning (DL) techniques involving fine-tuning large numbers of model parameters
have delivered impressive performance on the task of discriminating between language …

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 …

Ethical considerations in the early detection of Alzheimer's disease using speech and AI

U Petti, R Nyrup, JM Skopek, A Korhonen - Proceedings of the 2023 …, 2023 - dl.acm.org
While recent studies indicate that AI could play an important role in detecting early signs of
Alzheimer's disease in speech, this use of data from individuals with cognitive decline raises …