AIMC Topic: Alzheimer Disease
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Multi-Modal Diagnosis of Alzheimer's Disease Using Interpretable Graph Convolutional Networks.
IEEE transactions on medical imaging
Jan 2, 2025
The interconnection between brain regions in neurological disease encodes vital information for the advancement of biomarkers and diagnostics. Although graph convolutional networks are widely applied for discovering brain connection patterns that poi...
Identifying proteomic prognostic markers for Alzheimer's disease with survival machine learning: The Framingham Heart Study.
The journal of prevention of Alzheimer's disease
Jan 1, 2025
BACKGROUND: Protein abundance levels, sensitive to both physiological changes and external interventions, are useful for assessing the Alzheimer's disease (AD) risk and treatment efficacy. However, identifying proteomic prognostic markers for AD is c...
Deep learning predicts DNA methylation regulatory variants in specific brain cell types and enhances fine mapping for brain disorders.
Science advances
Jan 1, 2025
DNA methylation (DNAm) is essential for brain development and function and potentially mediates the effects of genetic risk variants underlying brain disorders. We present INTERACT, a transformer-based deep learning model to predict regulatory varian...
Artificial intelligence-enabled safety monitoring in Alzheimer's disease clinical trials.
The journal of prevention of Alzheimer's disease
Jan 1, 2025
BACKGROUND: Investigators conducting clinical trials have an ethical, scientific, and regulatory obligation to protect the safety of trial participants. Traditionally, safety monitoring includes manual review and coding of adverse event data by exper...
Deep Learning-Based Ion Channel Kinetics Analysis for Automated Patch Clamp Recording.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Dec 31, 2024
The patch clamp technique is a fundamental tool for investigating ion channel dynamics and electrophysiological properties. This study proposes the first artificial intelligence framework for characterizing multiple ion channel kinetics of whole-cell...
Enhancing early detection of Alzheimer's disease through hybrid models based on feature fusion of multi-CNN and handcrafted features.
Scientific reports
Dec 28, 2024
Alzheimer's disease (AD) is a brain disorder that causes memory loss and behavioral and thinking problems. The symptoms of Alzheimer's are similar throughout its development stages, which makes it difficult to diagnose manually. Therefore, artificial...
A proficient approach for the classification of Alzheimer's disease using a hybridization of machine learning and deep learning.
Scientific reports
Dec 28, 2024
Alzheimer's disease (AD) is a neurodegenerative disorder. It causes progressive degeneration of the nervous system, affecting the cognitive ability of the human brain. Over the past two decades, neuroimaging data from Magnetic Resonance Imaging (MRI)...
Interpretable machine learning-driven biomarker identification and validation for Alzheimer's disease.
Scientific reports
Dec 28, 2024
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by limited effective treatments, underscoring the critical need for early detection and diagnosis to improve intervention outcomes. This study integrates various bioinformatics me...
Proteome profiling of cerebrospinal fluid using machine learning shows a unique protein signature associated with APOE4 genotype.
Aging cell
Dec 25, 2024
Proteome changes associated with APOE4 variant carriage that are independent of Alzheimer's disease (AD) pathology and diagnosis are unknown. This study investigated APOE4 proteome changes in people with AD, mild cognitive impairment, and no impairme...
3-Dimensional morphological characterization of neuroretinal microglia in Alzheimer's disease via machine learning.
Acta neuropathologica communications
Dec 24, 2024
Alzheimer's Disease (AD) is a debilitating neurodegenerative disease that affects 47.5 million people worldwide. AD is characterised by the formation of plaques containing extracellular amyloid-β (Aβ) and neurofibrillary tangles composed of hyper-pho...
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