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
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Anatomically interpretable deep learning of brain age captures domain-specific cognitive impairment.

The gap between chronological age (CA) and biological brain age, as estimated from magnetic resonanc...

Towards better interpretable and generalizable AD detection using collective artificial intelligence.

Alzheimer's Disease is the most common cause of dementia. Accurate diagnosis and prognosis of this d...

Application of machine learning techniques for dementia severity prediction from psychometric tests in the elderly population.

Previous research has shown the benefits of early detection and treatment of dementia. This detectio...

Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer's Disease.

Deep learning (DL) on brain magnetic resonance imaging (MRI) data has shown excellent performance in...

Predicting Genetic Disorder and Types of Disorder Using Chain Classifier Approach.

Genetic disorders are the result of mutation in the deoxyribonucleic acid (DNA) sequence which can b...

Automatic lesion detection and segmentation in F-flutemetamol positron emission tomography images using deep learning.

BACKGROUND: Beta amyloid in the brain, which was originally confirmed by post-mortem examinations, c...

Deep learning-based speech analysis for Alzheimer's disease detection: a literature review.

BACKGROUND: Alzheimer's disease has become one of the most common neurodegenerative diseases worldwi...

The usability and feasibility validation of the social robot MINI in people with dementia and mild cognitive impairment; a study protocol.

BACKGROUND: Social robots have demonstrated promising outcomes in terms of increasing the social hea...

VGG-TSwinformer: Transformer-based deep learning model for early Alzheimer's disease prediction.

BACKGROUND AND OBJECTIVE: Mild cognitive impairment (MCI) is a transitional state between normal agi...

Dementia Detection from Speech Using Machine Learning and Deep Learning Architectures.

Dementia affects the patient's memory and leads to language impairment. Research has demonstrated th...

Interpretable brain disease classification and relevance-guided deep learning.

Deep neural networks are increasingly used for neurological disease classification by MRI, but the n...

Dialogue agents for artificial intelligence-based conversational systems for cognitively disabled: a systematic review.

PURPOSE: We present a systematic literature review of dialogue agents for Artificial Intelligence (A...

Identifying an Optimal Neuroinflammation Treatment Using a Nanoligomer Discovery Engine.

Acute activation of innate immune response in the brain, or neuroinflammation, protects this vital o...

Zoom-In Neural Network Deep-Learning Model for Alzheimer's Disease Assessments.

Deep neural networks have been successfully applied to generate predictive patterns from medical and...

P-ResUnet: Segmentation of brain tissue with Purified Residual Unet.

Brain tissue of Magnetic Resonance Imaging is precisely segmented and quantified, which aids in the ...

Monitoring Amyloidogenesis with a 3D Deep-Learning-Guided Biolaser Imaging Array.

Amyloidogenesis is a critical hallmark for many neurodegenerative diseases and drug screening; howev...

GeneSelectML: a comprehensive way of gene selection for RNA-Seq data via machine learning algorithms.

Selection of differentially expressed genes (DEGs) is a vital process to discover the causes of dise...

Multi-stage classification of Alzheimer's disease from F-FDG-PET images using deep learning techniques.

The study aims to implement a convolutional neural network framework that uses the 18F-FDG PET modal...

Deep learning signature of brain [F]FDG PET associated with cognitive outcome of rapid eye movement sleep behavior disorder.

An objective biomarker to predict the outcome of isolated rapid eye movement sleep behavior disorder...

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