Latest AI and machine learning research in alzheimer's disease for healthcare professionals.
The research aims to understand Alzheimer's genetic and immune landscapes using the amalgamation of three technologies: artificial intelligence (GenAI), integrative bioinformatics, and single-cell analysis. First, the study aims to identify and characterize the significant genes associated with Alzheimer's disease (AD) using three GenAI models (GPT‑4o, Gemini model, and DeepSeek). After the genes ...
The most prevalent type of dementia and a progressive neurodegenerative disease, Alzheimer's disease has a major influence on day-to-day functioning due to memory loss, cognitive decline, and behavioral problems. By using synchrosqueezing representations of EEG signals classified by fine-tuned pre-trained convolutional neural networks, this paper presents an EEG-based classification model for Alzh...
Alzheimer's Disease (AD) as one of the most prevalent neurodegenerative disorders worldwide, characterized by significant memory and cognitive decline...
BackgroundNeuroinflammation actively contributes to the pathophysiology of Alzheimer's disease (AD); however, the value of neuroinflammatory biomarker...
Dual-task composed of gait or stepping tasks combined with cognitive tasks has been well-established as valuable tools for detecting neurocognitive di...
Early and accurate diagnosis of Alzheimer's disease (AD) is crucial for effective treatment. While the integration of deep learning techniques for AD ...
Detecting Alzheimer's disease (AD) in its earliest stages, particularly during an onset of Mild Cognitive Impairment (MCI), remains challenging due to...
The increases in the older population, the prevalence of dementia, and the resulting social costs are burdensome to individuals, families, and the nat...
A growing body of literature has examined the impact of neighborhood characteristics on Alzheimer's disease (AD) dementia, yet the spatial variability...
BACKGROUND: Diabetes mellitus, characterized by chronic glucose dysregulation, significantly increases the risk of neurological disorders such as cogn...
BACKGROUND & OBJECTIVE: Alzheimer's Disease (AD) patients at multiple stages of disease progression have a high prevalence of seizures. However, wheth...
Alzheimer's disease (AD) is a neurodegenerative disorder that requires early diagnosis for effective management. However, issues with currently availa...
In this paper, we propose a deep super-resolution generative adversarial network (DSR-GAN) combined with a convolutional neural network (CNN) model de...
Alzheimer's disease (AD) represents a significant challenge due to its progressive neurodegenerative impact, particularly within an aging global demog...
BACKGROUND: The use of socially assistive robots in dementia care is growing, aimed at improving patient well-being and alleviating caregiver burden. ...
BACKGROUND: Sepsis, a life-threatening condition driven by dysregulated host responses to infection, is associated with long-term cognitive impairment...
BACKGROUND: The allelic variations of the apolipoprotein E (APOE) gene play a critical role in regulating lipid metabolism and significantly impact ca...
INTRODUCTION: At the present time, clinical detection of individuals who have amyloid in their brain is not possible without expensive biomarkers. The...
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the accumulation of amyloid plaques and neurofibrillary tangles in the brain...
BACKGROUND: Alzheimer's disease (AD) might impact the complexity of cerebral cortex, and the underlying biological mechanisms responsible for cortical...