AIMC Topic: Alzheimer Disease
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HEDDI-Net: heterogeneous network embedding for drug-disease association prediction and drug repurposing, with application to Alzheimer's disease.
Journal of translational medicine
Feb 1, 2025
BACKGROUND: The traditional process of developing new drugs is time-consuming and often unsuccessful, making drug repurposing an appealing alternative due to its speed and safety. Graph neural networks (GCNs) have emerged as a leading approach for pr...
Integrating neuroscience and artificial intelligence: EEG analysis using ensemble learning for diagnosis Alzheimer's disease and frontotemporal dementia.
Journal of neuroscience methods
Jan 31, 2025
BACKGROUND: Alzheimer's disease (AD) and frontotemporal dementia (FTD) are both progressive neurological disorders that affect the elderly. Distinguishing between individuals suffering from these two diseases in the early stages can be quite challeng...
Identification of therapeutic targets for Alzheimer's Disease Treatment using bioinformatics and machine learning.
Scientific reports
Jan 31, 2025
Alzheimer's disease (AD) is a complex neurodegenerative disorder that currently lacks effective treatment options. This study aimed to identify potential therapeutic targets for the treatment of AD using comprehensive bioinformatics methods and machi...
Predicting conversion in cognitively normal and mild cognitive impairment individuals with machine learning: Is the CSF status still relevant?
Alzheimer's & dementia : the journal of the Alzheimer's Association
Jan 30, 2025
INTRODUCTION: Machine learning (ML) helps diagnose the mild cognitive impairment-Alzheimer's disease (MCI-AD) spectrum. However, ML is fed with data unavailable in standard clinical practice. Thus, we tested a novel multi-step ML approach to predict ...
Preclinical Cognitive Markers of Alzheimer Disease and Early Diagnosis Using Virtual Reality and Artificial Intelligence: Literature Review.
JMIR medical informatics
Jan 28, 2025
BACKGROUND: This review explores the potential of virtual reality (VR) and artificial intelligence (AI) to identify preclinical cognitive markers of Alzheimer disease (AD). By synthesizing recent studies, it aims to advance early diagnostic methods t...
Alzheimer's disease: an integrative bioinformatics and machine learning analysis reveals glutamine metabolism-associated gene biomarkers.
BMC pharmacology & toxicology
Jan 28, 2025
BACKGROUND: Alzheimer's disease (AD), a hallmark of age-related cognitive decline, is defined by its unique neuropathology. Metabolic dysregulation, particularly involving glutamine (Gln) metabolism, has emerged as a critical but underexplored aspect...
Natural language processing-based classification of early Alzheimer's disease from connected speech.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Jan 27, 2025
INTRODUCTION: The automated analysis of connected speech using natural language processing (NLP) emerges as a possible biomarker for Alzheimer's disease (AD). However, it remains unclear which types of connected speech are most sensitive and specific...
An unsupervised learning approach for clustering joint trajectories of Alzheimer's disease biomarkers: An application to ADNI Data.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Jan 27, 2025
INTRODUCTION: Current models of Alzheimer's disease (AD) progression assume a common pattern and pathology, oversimplifying the heterogeneity of clinical AD.
Alzheimer's Disease: Exploring Pathophysiological Hypotheses and the Role of Machine Learning in Drug Discovery.
International journal of molecular sciences
Jan 24, 2025
Alzheimer's disease (AD) is a major neurodegenerative dementia, with its complex pathophysiology challenging current treatments. Recent advancements have shifted the focus from the traditionally dominant amyloid hypothesis toward a multifactorial und...
Enhanced detection of mild cognitive impairment in Alzheimer's disease: a hybrid model integrating dual biomarkers and advanced machine learning.
BMC geriatrics
Jan 23, 2025
Alzheimer's disease (AD) is a complex, progressive, and irreversible neurodegenerative disorder marked by cognitive decline and memory loss. Early diagnosis is the most effective strategy to slow the disease's progression. Mild Cognitive Impairment (...
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