Neurology

Dementia

Latest AI and machine learning research in dementia for healthcare professionals.

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γ neuromodulations: unraveling biomarkers for neurological and psychiatric disorders.

γ neuromodulation has emerged as a promising strategy for addressing neurological and psychiatric di...

Association of peripheral immune markers with brain age and dementia risk estimated using deep learning methods.

BACKGROUND: The peripheral immune system is essential for maintaining central nervous system homeost...

Novel insights from comprehensive analysis: The role of cuproptosis and peripheral immune infiltration in Alzheimer's disease.

BACKGROUND: Cuproptosis is increasingly recognized as an essential factor in the pathological proces...

Machine learning-based prediction of amyloid positivity using early-phase F-18 flutemetamol PET.

BackgroundPrevious studies have suggested that early-phase imaging of amyloid positron emission tomo...

Uncovering injury-specific proteomic signatures and neurodegenerative risks in single and repetitive traumatic brain injury.

Traumatic brain injury (TBI) is a major public health concern associated with an increased risk of n...

AI-driven discovery of brain-penetrant Galectin-3 inhibitors for Alzheimer's disease therapy.

Galectin-3 (Gal-3) has emerged as a critical regulator of neuroinflammation and a promising therapeu...

The Rapid Online Cognitive Assessment for the Detection of Neurocognitive Disorder: Open-Label Study.

BACKGROUND: The rising prevalence of dementia necessitates a scalable solution to cognitive screenin...

Perspectives and Experiences of Family Caregivers Using Supportive Mobile Apps in Dementia Care: Meta-Synthesis of Qualitative Research.

BACKGROUND: Supportive mobile apps are effective tools for family caregivers of persons with dementi...

Explainable AI predicting Alzheimer's disease with latent multimodal deep neural networks.

PURPOSE: Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cogni...

Alzheimer's disease digital biomarkers multidimensional landscape and AI model scoping review.

As digital biomarkers gain traction in Alzheimer's disease (AD) diagnosis, understanding recent adva...

Discovery of Novel Anti-Acetylcholinesterase Peptides Using a Machine Learning and Molecular Docking Approach.

OBJECTIVE: Alzheimer's disease poses a significant threat to human health. Currenttherapeutic medici...

Optimizing Dementia Diagnosis Through Distance-Correlation Feature Space and Dimensionality Reduction.

The reduction of dimensionality in machine learning and artificial intelligence problems constitutes...

Massively parallel genetic perturbation suggests the energetic structure of an amyloid-β transition state.

Amyloid aggregates are pathological hallmarks of many human diseases, but how soluble proteins nucle...

An ensemble-based 3D residual network for the classification of Alzheimer's disease.

Alzheimer's disease (AD) is a common type of dementia, with mild cognitive impairment (MCI) being a ...

Multivariate brain morphological patterns across mood disorders: key roles of frontotemporal and cerebellar areas.

BACKGROUND: Differentiating major depressive disorder (MDD) from bipolar disorder (BD) remains a sig...

Detecting label noise in longitudinal Alzheimer's data with explainable artificial intelligence.

Reliable classification of cognitive states in longitudinal Alzheimer's Disease (AD) studies is crit...

SLR: A Modified Logistic Regression Model with Sinkhorn Divergence for Alzheimer's Disease Classification.

Logistic regression is a widely used model in machine learning, particularly as a baseline for binar...

Early Alzheimer's Detection Through Voice Analysis: Harnessing Locally Deployable LLMs via , a privacy-preserving diagnostic system.

Diagnosing Alzheimer's Disease (AD) early and cost-effectively is crucial. Recent advancements in La...

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