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Dementia

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Machine Learning Approaches for Dementia Detection Through Speech and Gait Analysis: A Systematic Literature Review.

Journal of Alzheimer's disease : JAD
BACKGROUND: Dementia is a general term for several progressive neurodegenerative disorders including Alzheimer's disease. Timely and accurate detection is crucial for early intervention. Advancements in artificial intelligence present significant pot...

Geodesic shape regression based deep learning segmentation for assessing longitudinal hippocampal atrophy in dementia progression.

NeuroImage. Clinical
Longitudinal hippocampal atrophy is commonly used as progressive marker assisting clinical diagnose of dementia. However, precise quantification of the atrophy is limited by longitudinal segmentation errors resulting from MRI artifacts across multipl...

No playing around with robots? Ambivalent attitudes toward the use of Paro in elder care.

Nursing inquiry
This paper explores the ways in which health care professionals, family carers, and older persons expressed attitudes and opinions on using Paro, a social robot designed to stimulate patients with dementia. Thereafter, we critically evaluate existing...

A multimodal machine learning model for predicting dementia conversion in Alzheimer's disease.

Scientific reports
Alzheimer's disease (AD) accounts for 60-70% of the population with dementia. Mild cognitive impairment (MCI) is a diagnostic entity defined as an intermediate stage between subjective cognitive decline and dementia, and about 10-15% of people annual...

Using AI-Based Technologies to Help Nurses Detect Behavioral Disorders: Narrative Literature Review.

JMIR nursing
BACKGROUND: The behavioral and psychological symptoms of dementia (BPSD) are common among people with dementia and have multiple negative consequences. Artificial intelligence-based technologies (AITs) have the potential to help nurses in the early p...

Predicting changes in brain metabolism and progression from mild cognitive impairment to dementia using multitask Deep Learning models and explainable AI.

NeuroImage
BACKGROUND: The prediction of Alzheimer's disease (AD) progression from its early stages is a research priority. In this context, the use of Artificial Intelligence (AI) in AD has experienced a notable surge in recent years. However, existing investi...

Multimodal deep learning for dementia classification using text and audio.

Scientific reports
Dementia is a progressive neurological disorder that affects the daily lives of older adults, impacting their verbal communication and cognitive function. Early diagnosis is important to enhance the lifespan and quality of life for affected individua...

Self-Explainable Graph Neural Network for Alzheimer Disease and Related Dementias Risk Prediction: Algorithm Development and Validation Study.

JMIR aging
BACKGROUND: Alzheimer disease and related dementias (ADRD) rank as the sixth leading cause of death in the United States, underlining the importance of accurate ADRD risk prediction. While recent advancements in ADRD risk prediction have primarily re...

AI-based differential diagnosis of dementia etiologies on multimodal data.

Nature medicine
Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that har...