AIMC Topic: Alzheimer Disease

Clear Filters Showing 91 to 100 of 962 articles

Dense convolution-based attention network for Alzheimer's disease classification.

Scientific reports Feb 17, 2025
Recently, deep learning-based medical image classification models have made substantial advancements. However, many existing models prioritize performance at the cost of efficiency, limiting their practicality in clinical use. Traditional Convolution...
Alzheimer Disease Deep Learning ROC Curve Magnetic Resonance Imaging Humans Neural Networks, Computer
View on PubMed DOI

Stacked CNN-based multichannel attention networks for Alzheimer disease detection.

Scientific reports Feb 17, 2025
Alzheimer's Disease (AD) is a progressive condition of a neurological brain disorder recognized by symptoms such as dementia, memory loss, alterations in behaviour, and impaired reasoning abilities. Recently, many researchers have been working to dev...
Alzheimer Disease Humans Deep Learning Neural Networks, Computer Magnetic Resonance Imaging
View on PubMed DOI

Graph and Multi-Level Sequence Fusion Learning for Predicting the Molecular Activity of BACE-1 Inhibitors.

International journal of molecular sciences Feb 16, 2025
The development of BACE-1 (β-site amyloid precursor protein cleaving enzyme 1) inhibitors is a crucial focus in exploring early treatments for Alzheimer's disease (AD). Recently, graph neural networks (GNNs) have demonstrated significant advantages i...
Amyloid Precursor Protein Secretases Aspartic Acid Endopeptidases Neural Networks, Computer Alzheimer Disease Humans Enzyme Inhibitors Machine Learning
View on PubMed DOI

Exploring Potential Medications for Alzheimer's Disease with Psychosis by Integrating Drug Target Information into Deep Learning Models: A Data-Driven Approach.

International journal of molecular sciences Feb 14, 2025
Approximately 50% of Alzheimer's disease (AD) patients develop psychotic symptoms, leading to a subtype known as psychosis in AD (AD + P), which is associated with accelerated cognitive decline compared to AD without psychosis. Currently, no FDA-appr...
Antipsychotic Agents Psychotic Disorders Humans Aged Male Alzheimer Disease Electronic Health Records Deep Learning Female
View on PubMed DOI

Reducing inference cost of Alzheimer's disease identification using an uncertainty-aware ensemble of uni-modal and multi-modal learners.

Scientific reports Feb 14, 2025
While multi-modal deep learning approaches trained using magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG PET) data have shown promise in the accurate identification of Alzheimer's disease, their clinical appl...
Humans Brain Deep Learning Positron-Emission Tomography Fluorodeoxyglucose F18 Uncertainty Magnetic Resonance Imaging Alzheimer Disease
View on PubMed DOI

Interpretable AI for inference of causal molecular relationships from omics data.

Science advances Feb 14, 2025
The discovery of molecular relationships from high-dimensional data is a major open problem in bioinformatics. Machine learning and feature attribution models have shown great promise in this context but lack causal interpretation. Here, we show that...
Alzheimer Disease Algorithms Humans Gene Regulatory Networks Machine Learning Computational Biology
View on PubMed DOI

Hybrid-RViT: Hybridizing ResNet-50 and Vision Transformer for Enhanced Alzheimer's disease detection.

PloS one Feb 14, 2025
Alzheimer's disease (AD) is a leading cause of disability worldwide. Early detection is critical for preventing progression and formulating effective treatment plans. This study aims to develop a novel deep learning (DL) model, Hybrid-RViT, to enhanc...
Magnetic Resonance Imaging Brain Humans Deep Learning Alzheimer Disease Neural Networks, Computer
View on PubMed DOI

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

Computational biology and chemistry Feb 13, 2025
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...
Brain Deep Learning Fuzzy Logic Alzheimer Disease Image Processing, Computer-Assisted Humans Neural Networks, Computer
View on PubMed DOI

A quantitatively interpretable model for Alzheimer's disease prediction using deep counterfactuals.

NeuroImage Feb 13, 2025
Deep learning (DL) for predicting Alzheimer's disease (AD) has provided timely intervention in disease progression yet still demands attentive interpretability to explain how their DL models make definitive decisions. Counterfactual reasoning has rec...
Image Interpretation, Computer-Assisted Gray Matter Male Disease Progression Magnetic Resonance Imaging Alzheimer Disease Deep Learning Brain Female Aged Humans
View on PubMed DOI

Prediction of cognitive conversion within the Alzheimer's disease continuum using deep learning.

Alzheimer's research & therapy Feb 13, 2025
BACKGROUND: Early diagnosis and accurate prognosis of cognitive decline in Alzheimer's disease (AD) is important to timely assignment to optimal treatment modes. We aimed to develop a deep learning model to predict cognitive conversion to guide re-as...
Disease Progression Deep Learning Cognitive Dysfunction Aged, 80 and over Male Alzheimer Disease Neuroimaging Neuropsychological Tests Cohort Studies Longitudinal Studies Humans Female Aged Prognosis
View on PubMed DOI
Popular Topics
Recent Journals