AI Medical Compendium Topic:
Alzheimer Disease

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Deep-Diffeomorphic Networks for Conditional Brain Templates.

Human brain mapping
Deformable brain templates are an important tool in many neuroimaging analyses. Conditional templates (e.g., age-specific templates) have advantages over single population templates by enabling improved registration accuracy and capturing common proc...

Identification and prioritization of disease candidate genes using biomedical named entity recognition and random forest classification.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: The elucidation of candidate genes is fundamental to comprehending intricate diseases, vital for early diagnosis, personalized treatment, and drug discovery. Traditional Disease Gene Identification methods encounter limitati...

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

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Alzheimer's disease (AD) significantly threatens community well-being and healthcare resource allocation due to its high incidence and mortality. Therefore, early detection and intervention are crucial for reducing AD-relate...

Taylor-dingo optimized RP-net for segmentation toward Alzheimer's disease detection and classification using deep learning.

Computational biology and chemistry
Alzheimer's Disease (AD) is a significant cause of mortality in elderly people. The diagnosing and classification of AD using conventional manual operation is a challenging issue. Here, a novel scheme, namely Recurrent Prototypical Network with Taylo...

Alzheimer's disease classification using hybrid loss Psi-Net segmentation and a new hybrid network model.

Computational biology and chemistry
Alzheimer's disease (AD) is a type of brain disorder that is becoming more prevalent worldwide. It is a progressive and irreversible condition that gradually impairs memory and cognitive abilities, eventually making it difficult to perform even basic...

MRI-based diagnostic model for Alzheimer's disease using 3D-ResNet.

Biomedical physics & engineering express
Alzheimer's disease (AD), a progressive neurodegenerative disorder, is the leading cause of dementia worldwide and remains incurable once it begins. Therefore, early and accurate diagnosis is essential for effective intervention. Leveraging recent ad...

Ethics From the Outset: Incorporating Ethical Considerations into the Artificial Intelligence and Technology Collaboratories for Aging Research Pilot Projects.

The journals of gerontology. Series A, Biological sciences and medical sciences
There is an urgent need to develop tools to enable older adults to live healthy, independent lives for as long as possible. To address this need, the National Institute on Aging (NIA) Artificial Intelligence and Technology Collaboratories (AITCs) for...

Early detection of Alzheimer's disease using deep learning methods.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Alzheimer's disease (AD), a leading cause of dementia, requires early detection for effective intervention. This study employs AI to analyze multimodal datasets, including clinical, biomarker, and neuroimaging data, using hybrid deep le...

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

Computers in biology and medicine
In recent years, machine learning-based handwriting analysis has emerged as a valuable tool for supporting the early diagnosis of Alzheimer's disease and predicting its progression. Traditional approaches represent handwriting tasks using a single fe...

Advanced convolutional neural network with attention mechanism for Alzheimer's disease classification using MRI.

Computers in biology and medicine
This paper introduces a novel convolutional neural network model with an attention mechanism to advance Alzheimer disease (AD) classification using Magnetic Resonance Imaging (MRI). The model architecture is meticulously crafted to enhance feature ex...