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 232-252 of 11,597 articles
Advanced convolutional neural network with attention mechanism for Alzheimer's disease classification using MRI.

This paper introduces a novel convolutional neural network model with an attention mechanism to adva...

A Machine Learning Approach to Predict Cognitive Decline in Alzheimer Disease Clinical Trials.

BACKGROUND AND OBJECTIVES: Among the participants of Alzheimer disease (AD) treatment trials, 40% do...

Ensemble network using oblique coronal MRI for Alzheimer's disease diagnosis.

Alzheimer's disease (AD) is a primary degenerative brain disorder commonly found in the elderly, Mil...

Employing artificial bee and ant colony optimization in machine learning techniques as a cognitive neuroscience tool.

Higher education is essential because it exposes students to a variety of areas. The academic perfor...

New approach to specific Alzheimer's disease diagnosis based on plasma biomarkers in a cognitive disorder cohort.

BACKGROUND: The validation of a combination of plasma biomarkers and demographic variables is requir...

Class balancing diversity multimodal ensemble for Alzheimer's disease diagnosis and early detection.

Alzheimer's disease (AD) poses significant global health challenges due to its increasing prevalence...

Transforming neurodegenerative disorder care with machine learning: Strategies and applications.

Neurodegenerative diseases (NDs), characterized by progressive neuronal degeneration and manifesting...

Uncovering hidden subtypes in dementia: An unsupervised machine learning approach to dementia diagnosis and personalization of care.

OBJECTIVE: Dementia represents a growing public health challenge, affecting an increasing number of ...

Machine learning reveals distinct neuroanatomical signatures of cardiovascular and metabolic diseases in cognitively unimpaired individuals.

Comorbid cardiovascular and metabolic risk factors (CVM) differentially impact brain structure and i...

Using Deep Learning to Perform Automatic Quantitative Measurement of Masseter and Tongue Muscles in Persons With Dementia: Cross-Sectional Study.

BACKGROUND: Sarcopenia (loss of muscle mass and strength) increases adverse outcomes risk and contri...

Weighted Multi-Modal Contrastive Learning Based Hybrid Network for Alzheimer's Disease Diagnosis.

Multiple imaging modalities and specific proteins in the cerebrospinal fluid, providing a comprehens...

Reevaluating feature importance in machine learning: concerns regarding SHAP interpretations in the context of the EU artificial intelligence act.

This paper critically examines the analysis conducted by Maußner et al. on AI analysis, particularly...

Stages prediction of Alzheimer's disease with shallow 2D and 3D CNNs from intelligently selected neuroimaging data.

Detection of Alzheimer's Disease (AD) is critical for successful diagnosis and treatment, involving ...

Effectiveness of Chatbot interventions for reducing caregiver burden: Protocol for a systematic review and meta-analysis.

This protocol outlines a systematic review and meta-analysis examining the effectiveness of fully au...

Neuropsychological tests and machine learning: identifying predictors of MCI and dementia progression.

BACKGROUND: Early prediction of progression in dementia is of major importance for providing patient...

A comprehensive interpretable machine learning framework for mild cognitive impairment and Alzheimer's disease diagnosis.

An interpretable machine learning (ML) framework is introduced to enhance the diagnosis of Mild Cogn...

Dementia Overdiagnosis in Younger, Higher Educated Individuals Based on MMSE Alone: Analysis Using Deep Learning Technology.

BACKGROUND: Dementia is a multifaceted disorder that affects cognitive function, necessitating accur...

Intelligent Robot Interventions for People With Dementia: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: The application of intelligent robots in therapy is becoming more and more important for...

Machine learning to detect Alzheimer's disease with data on drugs and diagnoses.

BACKGROUND: Integrating machine learning with medical records offers potential for early detection o...

Comparison of Deep Learning and Traditional Machine Learning Models for Predicting Mild Cognitive Impairment Using Plasma Proteomic Biomarkers.

Mild cognitive impairment (MCI) is a clinical condition characterized by a decline in cognitive abil...

MCNEL: A multi-scale convolutional network and ensemble learning for Alzheimer's disease diagnosis.

BACKGROUND AND OBJECTIVE: Alzheimer's disease (AD) significantly threatens community well-being and ...

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