Neurology

Dementia

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

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A combination of 3-D discrete wavelet transform and 3-D local binary pattern for classification of mild cognitive impairment.

BACKGROUND: The detection of Alzheimer's Disease (AD) in its formative stages, especially in Mild Co...

Measuring the impact of age, gender and dementia on communication-robot interventions in residential care homes.

AIM: The primary aim of this study was to examine the impact of age, gender and the stage of dementi...

Multimodal Data Analysis of Alzheimer's Disease Based on Clustering Evolutionary Random Forest.

Alzheimer's disease (AD) has become a severe medical challenge. Advances in technologies produced hi...

Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease-informed machine-learning.

INTRODUCTION: Developing cross-validated multi-biomarker models for the prediction of the rate of co...

Deep Learning Prediction of Mild Cognitive Impairment using Electronic Health Records.

About 44.4 million people have been diagnosed with dementia worldwide, and it is estimated that this...

Modelling prognostic trajectories of cognitive decline due to Alzheimer's disease.

Alzheimer's disease (AD) is characterised by a dynamic process of neurocognitive changes from normal...

Shaping technologies for older adults with and without dementia: Reflections on ethics and preferences.

As a result of several years of European funding, progressive introduction of assistive technologies...

A survey on machine and statistical learning for longitudinal analysis of neuroimaging data in Alzheimer's disease.

BACKGROUND AND OBJECTIVES: Recently, longitudinal studies of Alzheimer's disease have gathered a sub...

Self-calibrated brain network estimation and joint non-convex multi-task learning for identification of early Alzheimer's disease.

Detection of early stages of Alzheimer's disease (AD) (i.e., mild cognitive impairment (MCI)) is imp...

Ambivert degree identifies crucial brain functional hubs and improves detection of Alzheimer's Disease and Autism Spectrum Disorder.

Functional modules in the human brain support its drive for specialization whereas brain hubs act as...

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment.

Mild cognitive impairment (MCI) is the first sign of dementia among elderly populations and its earl...

Dual-functional neural network for bilateral hippocampi segmentation and diagnosis of Alzheimer's disease.

PURPOSE: Knowing the course of Alzheimer's disease is very important to prevent the deterioration of...

Hypergraph based multi-task feature selection for multimodal classification of Alzheimer's disease.

Multi-modality based classification methods are superior to the single modality based approaches for...

Ethical concerns with the use of intelligent assistive technology: findings from a qualitative study with professional stakeholders.

BACKGROUND: Advances in artificial intelligence (AI), robotics and wearable computing are creating n...

A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer's disease.

Alzheimer's disease (AD) is a progressive and irreversible brain degenerative disorder. Mild cogniti...

A novel multi-modal machine learning based approach for automatic classification of EEG recordings in dementia.

Electroencephalographic (EEG) recordings generate an electrical map of the human brain that are usef...

Exploring the perceptions of people with dementia about the social robot PARO in a hospital setting.

New technology, such as social robots, opens up new opportunities in hospital settings. PARO, a robo...

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