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 211-231 of 11,597 articles
The future of Alzheimer's disease risk prediction: a systematic review.

BACKGROUND: Alzheimer's disease is the most prevalent kind of age-associated dementia among older ad...

Automated phenotyping of mild cognitive impairment and Alzheimer's disease and related dementias using electronic health records.

OBJECTIVES: Unstructured and structured data in electronic health records (EHR) are a rich source of...

IT: An interpretable transformer model for Alzheimer's disease prediction based on PET/MR images.

Alzheimer's disease (AD) represents a significant challenge due to its progressive neurodegenerative...

The role of machine learning in predicting titanium dioxide nanoparticles induced pulmonary pathology using transcriptomic biomarkers.

This study explores the application of machine learning (ML) in identifying transcriptomic changes a...

CLIC1 and IFITM2 expression in brain tissue correlates with cognitive impairment via immune dysregulation in sepsis and Alzheimer's disease.

BACKGROUND: Sepsis, a life-threatening condition driven by dysregulated host responses to infection,...

Assessing the cardioprotective effects of exercise in APOE mouse models using deep learning and photon-counting micro-CT.

BACKGROUND: The allelic variations of the apolipoprotein E (APOE) gene play a critical role in regul...

The Cognivue Amyloid Risk Measure (CARM): A Novel Method to Predict the Presence of Amyloid with Cognivue Clarity.

INTRODUCTION: At the present time, clinical detection of individuals who have amyloid in their brain...

Ensemble deep learning for Alzheimer's disease diagnosis using MRI: Integrating features from VGG16, MobileNet, and InceptionResNetV2 models.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the accumulation of amyloi...

The impact of Alzheimer's disease on cortical complexity and its underlying biological mechanisms.

BACKGROUND: Alzheimer's disease (AD) might impact the complexity of cerebral cortex, and the underly...

A fine-tuned convolutional neural network model for accurate Alzheimer's disease classification.

Alzheimer's disease (AD) is one of the primary causes of dementia in the older population, affecting...

DEMENTIA: A Hybrid Attention-Based Multimodal and Multi-Task Learning Framework With Expert Knowledge for Alzheimer's Disease Assessment From Speech.

The prevalence of Alzheimer's disease (AD) is rising annually, imposing a severe burden on patients ...

LGG-NeXt: A Next Generation CNN and Transformer Hybrid Model for the Diagnosis of Alzheimer's Disease Using 2D Structural MRI.

Incurable Alzheimer's disease (AD) plagues many elderly people and families. It is important to accu...

Deep Geometric Learning With Monotonicity Constraints for Alzheimer's Disease Progression.

Alzheimer's disease (AD) is a devastating neurodegenerative condition that precedes progressive and ...

Patterns and Trends in Global Nursing Robotics Research: A Bibliometric Study.

The present study aimed to investigate the trends and research status of global nursing robot resea...

GCN-BBB: Deep Learning Blood-Brain Barrier (BBB) Permeability PharmacoAnalytics with Graph Convolutional Neural (GCN) Network.

The Blood-Brain Barrier (BBB) is a selective barrier between the Central Nervous System (CNS) and th...

Amyloid-β Deposition Prediction With Large Language Model Driven and Task-Oriented Learning of Brain Functional Networks.

Amyloid- positron emission tomography can reflect the Amyloid- protein deposition in the brain and t...

Identifying progression subphenotypes of Alzheimer's disease from large-scale electronic health records with machine learning.

OBJECTIVE: Identification of clinically meaningful subphenotypes of disease progression can enhance ...

Handwriting strokes as biomarkers for Alzheimer's disease prediction: A novel machine learning approach.

In recent years, machine learning-based handwriting analysis has emerged as a valuable tool for supp...

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