Geriatrics

Alzheimer's Disease

Latest AI and machine learning research in alzheimer's disease for healthcare professionals.

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Geriatrics Subcategories: Alzheimer's Disease Medicare
Showing 505-525 of 11,608 articles
E-BDL: Enhanced Band-Dependent Learning Framework for Augmented Radar Sensing.

Radar sensors, leveraging the Doppler effect, enable the nonintrusive capture of kinetic and physiol...

XAI-Based Assessment of the AMURA Model for Detecting Amyloid-β and Tau Microstructural Signatures in Alzheimer's Disease.

Brain microstructural changes already occur in the earliest phases of Alzheimer's disease (AD) as ev...

Neuropsychological and electrophysiological measurements for diagnosis and prediction of dementia: a review on Machine Learning approach.

INTRODUCTION: Emerging and advanced technologies in the field of Artificial Intelligence (AI) repres...

Disentangling brain atrophy heterogeneity in Alzheimer's disease: A deep self-supervised approach with interpretable latent space.

Alzheimer's disease (AD) is heterogeneous, but existing methods for capturing this heterogeneity thr...

Improving brain atrophy quantification with deep learning from automated labels using tissue similarity priors.

Brain atrophy measurements derived from magnetic resonance imaging (MRI) are a promising marker for ...

A Novel Implementation of a Social Robot for Sustainable Human Engagement in Homecare Services for Ageing Populations.

This research addresses the rapid aging phenomenon prevalent in Asian societies, which has led to a ...

Unbiased analysis of spatial learning strategies in a modified Barnes maze using convolutional neural networks.

Assessment of spatial learning abilities is central to behavioral neuroscience and a useful tool for...

A model for identifying potentially inappropriate medication used in older people with dementia: a machine learning study.

BACKGROUND: Older adults with dementia often face the risk of potentially inappropriate medication (...

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

BACKGROUND: Alzheimer disease and related dementias (ADRD) rank as the sixth leading cause of death ...

Artificial intelligence in Parkinson's disease: Early detection and diagnostic advancements.

Parkinson's disease (PD) is the second most common neurodegenerative disorder, globally affecting me...

AI driven analysis of MRI to measure health and disease progression in FSHD.

Facioscapulohumeral muscular dystrophy (FSHD) affects roughly 1 in 7500 individuals. While at the po...

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

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across et...

Predicting Alzheimer's disease from cognitive footprints in mid and late life: How much can register data and machine learning help?

BACKGROUND: Real-world data with decades-long medical records are increasingly available alongside t...

Structure focused neurodegeneration convolutional neural network for modelling and classification of Alzheimer's disease.

Alzheimer's disease (AD), the predominant form of dementia, is a growing global challenge, emphasizi...

A systematic literature review on the significance of deep learning and machine learning in predicting Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is the most prevalent cause of dementia, characterized by a ste...

Advances in Computational Biology for Diagnosing Neurodegenerative Diseases: A Comprehensive Review.

The numerous and varied forms of neurodegenerative illnesses provide a considerable challenge to con...

Predicting Alzheimer's Disease Progression Using a Versatile Sequence-Length-Adaptive Encoder-Decoder LSTM Architecture.

Detecting Alzheimer's disease (AD) accurately at an early stage is critical for planning and impleme...

Prediction of Alzheimer's disease progression within 6 years using speech: A novel approach leveraging language models.

INTRODUCTION: Identification of individuals with mild cognitive impairment (MCI) who are at risk of ...

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