Neurology

Dementia

Latest AI and machine learning research in dementia for healthcare professionals.

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Deciphering the role of lipid metabolism-related genes in Alzheimer's disease: a machine learning approach integrating Traditional Chinese Medicine.

BACKGROUND: Alzheimer's disease (AD) represents a progressive neurodegenerative disorder characteriz...

Machine learning reveals prominent spontaneous behavioral changes and treatment efficacy in humanized and transgenic Alzheimer's disease models.

Computer-vision and machine-learning (ML) approaches are being developed to provide scalable, unbias...

Graph neural networks for electroencephalogram analysis: Alzheimer's disease and epilepsy use cases.

Electroencephalography (EEG) is widely used as a non-invasive technique for the diagnosis of several...

A genetic programming Rician noise reduction and explainable deep learning model for Alzheimer's diseases severity prediction.

BACKGROUND: Degradation of magnetic resonance imaging (MRI) remains a challenging issue, with noise ...

An Ensemble Learning Algorithm for Cognitive Evaluation by an Immersive Virtual Reality Supermarket.

Early screening for Mild Cognitive Impairment (MCI) is crucial in delaying cognitive deterioration a...

Deep convolutional neural network-based identification and biological evaluation of MAO-B inhibitors.

Parkinson's disease (PD) is one of the most prominent motor disorder of adult-onset dementia connect...

A deep learning approach for non-invasive Alzheimer's monitoring using microwave radar data.

Over 50 million people globally suffer from Alzheimer's disease (AD), emphasizing the need for effic...

Pain Assessment for Patients with Dementia and Communication Impairment: Feasibility Study of the Usage of Artificial Intelligence-Enabled Wearables.

BACKGROUND: Recent studies on machine learning have shown the potential to provide new methods with ...

Explainability of CNN-based Alzheimer's disease detection from online handwriting.

With over 55 million people globally affected by dementia and nearly 10 million new cases reported a...

Can robots lie? A posthumanist approach to robotic animals and deceptive practices in dementia care.

Robotic animals are designed to resemble real, living animals, but at the same time, dementia care g...

3-1-3 Weight averaging technique-based performance evaluation of deep neural networks for Alzheimer's disease detection using structural MRI.

Alzheimer's disease (AD) is a progressive neurological disorder. It is identified by the gradual shr...

Early diagnosis of Alzheimer's Disease based on multi-attention mechanism.

Alzheimer's Disease is a neurodegenerative disorder, and one of its common and prominent early sympt...

AI-driven innovations in Alzheimer's disease: Integrating early diagnosis, personalized treatment, and prognostic modelling.

Alzheimer's disease (AD) presents a significant challenge in neurodegenerative research and clinical...

Criticality of Nursing Care for Patients With Alzheimer's Disease in the ICU: Insights From MIMIC III Dataset.

Alzheimer's disease (AD) patients admitted to intensive care units (ICUs) exhibit varying survival o...

Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults: Study of Domain Adaptation and Deep Learning.

BACKGROUND: Cognitive impairment and dementia pose a significant challenge to the aging population, ...

A Novel Method to Identify Mild Cognitive Impairment Using Dynamic Spatio-Temporal Graph Neural Network.

Resting-state functional magnetic resonance imaging (rs-fMRI) has been widely used in the identifica...

Mild cognitive impairment prediction based on multi-stream convolutional neural networks.

BACKGROUND: Mild cognitive impairment (MCI) is the transition stage between the cognitive decline ex...

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