Latest AI and machine learning research in alzheimer's disease for healthcare professionals.
BACKGROUND: To investigate the radiomics features of the hippocampus and the amygdala subregions in FDG-PET images that can best differentiate Mild Cognitive Impairment (MCI), Alzheimer’s Disease (AD), and healthy patients. METHODS: Baseline FDG-PET data from 555 participants in the ADNI dataset were analyzed, comprising 189 cognitively normal (CN) individuals, 201 with MCI, and 165 with AD. We ex...
BACKGROUND: Vascular dementia (VaD), known for cognitive issues and cerebrovascular irregularities, is a common dementia type, but its molecular underpinnings are still uncertain. Emerging evidence indicates that gut microbiota and their metabolites affect neuroinflammation and cerebrovascular health via the gut-brain axis, suggesting potential microbiota-based interventions. METHODS: In this stud...
Accurate, early-stage staging of Alzheimer's disease (AD) is critical for therapeutic intervention but is hampered by data privacy regulations, multim...
Alzheimer's disease (AD) is an irreversible neurodegenerative disorder whose progression is closely associated with time. However, most diagnostic mod...
Currently a large number of people living in long-term care facilities suffer from cognitive disorders such as dementia. In this context, new robotic ...
Insulating sheaths of myelin accelerate neuronal communication in the mammalian brain. Oligodendrocytes that produce myelin are generated throughout l...
BackgroundNeuroimaging-derived brain age is a promising biomarker of early neurodegeneration, but methodological variation in machine learning (ML) al...
BACKGROUND: Sensor-based footwear is increasingly discussed as a promising tool for mobility monitoring and fall-risk assessment, yet its applicabilit...
Quantitative susceptibility mapping (QSM) on MRI quantifies tissue magnetic susceptibility, which increases with iron accumulation, myelin loss, and n...
BACKGROUND: Automated approaches to cognitive impairment screening may soon achieve sufficient levels of accuracy for clinical implementation but they...
Integrating resting-state functional magnetic resonance imaging (rs-fMRI) and phenotypic data is a promising way to build a comprehensive population g...
BACKGROUND: Artificial intelligence (AI) is increasingly applied to health care, yet concerns about fairness persist, particularly in relation to soci...
AIM: APOE genotype may affect statin therapy response. We conducted a meta-analysis to update and quantify this association across various outcomes. M...
Pathological and neuroimaging changes in the cerebellum of Alzheimer's disease (AD) patients have been well documented. However, the changes in cerebe...
The brain is a highly complex organ, exhibiting a highly dynamic chemical environment, playing crucial role in coordinating pathophysiological process...
Single-cell and single-nucleus RNA sequencing are used to reveal heterogeneity in cells, showing a growing potential for precision and personalized me...
Alzheimer's disease (AD) classification using machine learning has increasingly relied on multimodal inputs such as Magnetic Resonance Imaging (MRI), ...
Deep learning models leveraging human activity data, such as gait, have shown promise for dementia prediction. However, their limited interpretability...
The detection of Alzheimer's Disease (AD) using structural Magnetic Resonance Imaging (MRI) and Machine Learning (ML) often focuses on late-stage atro...