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 1471-1491 of 11,708 articles
The Impact of Artificial Intelligence in Reducing the Cost of Dementia: A Scoping Review.

INTRODUCTION: Dementia is a major cause of disability among the elderly, imposing significant financ...

Applying Data Mining to Predict Perceived Benefits Risks of Robotics at Home for Dementia Caregiving Among African American Families.

We used data mining to predict the attitudes of 527 caregivers towards the pros and cons of using ro...

Machine learning reveals connections between preclinical type 2 diabetes subtypes and brain health.

Previous research has established type 2 diabetes mellitus as a significant risk factor for various ...

[Machine learning models established to distinguish OA and RA based on immune factors in the knee joint fluid].

Objective Based on 25 indicators including immune factors, cell count classification, and smear resu...

Dynamic and Static Structure-Function Coupling With Machine Learning for the Early Detection of Alzheimer's Disease.

The progression of Alzheimer's disease (AD) involves complex changes in brain structure and function...

Evaluating Traditional, Deep Learning and Subfield Methods for Automatically Segmenting the Hippocampus From MRI.

Given the relationship between hippocampal atrophy and cognitive impairment in various pathological ...

Predicting explainable dementia types with LLM-aided feature engineering.

MOTIVATION: The integration of Machine Learning and Artificial Intelligence (AI) into healthcare has...

MUTATE: a human genetic atlas of multiorgan artificial intelligence endophenotypes using genome-wide association summary statistics.

Artificial intelligence (AI) has been increasingly integrated into imaging genetics to provide inter...

A deep-learning retinal aging biomarker for cognitive decline and incident dementia.

INTRODUCTION: The utility of retinal photography-derived aging biomarkers for predicting cognitive d...

Developing and validating a prediction tool for cerebral amyloid angiopathy neuropathological severity.

INTRODUCTION: Cerebral amyloid angiopathy (CAA) is a cerebrovascular condition, the severity of whic...

SBERO: Skill Al-Biruni Earth Radius Optimization for Alzheimer's Disease Classification Using Magnetic Resonance Image.

Alzheimer's disease (AD) is the most prevalent form of dementia, characterized by progressive memory...

Deep learning-based cell-specific gene regulatory networks inferred from single-cell multiome data.

Gene regulatory networks (GRNs) provide a global representation of how genetic/genomic information i...

[Classification of Alzheimer's disease based on multi-example learning and multi-scale feature fusion].

Alzheimer's disease (AD) classification models usually segment the entire brain image into voxel blo...

Diagnosis of Alzheimer's disease using FusionNet with improved secretary bird optimization algorithm for optimal MK-SVM based on imaging genetic data.

Alzheimer's disease is an irreversible central neurodegenerative disease, and early diagnosis of Alz...

Machine learning prediction of tau-PET in Alzheimer's disease using plasma, MRI, and clinical data.

INTRODUCTION: Tau positron emission tomography (PET) is a reliable neuroimaging technique for assess...

AggNet: Advancing protein aggregation analysis through deep learning and protein language model.

Protein aggregation is critical to various biological and pathological processes. Besides, it is als...

Classification and Pixel Change Detection of Brain Tumor Using Adam Kookaburra Optimization-Based Shepard Convolutional Neural Network.

The uncommon growth of cells in the brain is termed as brain tumor. To identify chronic nerve proble...

A machine learning approach to automate microinfarct and microhemorrhage screening in hematoxylin and eosin-stained human brain tissues.

Microinfarcts and microhemorrhages are characteristic lesions of cerebrovascular disease. Although m...

Sleep efficiency in community-dwelling persons living with dementia: exploratory analysis using machine learning.

STUDY OBJECTIVES: Sleep disturbances lead to negative health outcomes and caregiver burden, particul...

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