Alzheimer's Disease

Scan-wise generalized PET denoising with contrastive adversarial learning.

Objective.Deep learning has significantly advanced low-count positron emission tomography (PET) denoising. However, models trained on specific distributions often yield biased outputs when applied to scans with different activity distributions caused by anatomical and physiological variations (distribution shifts). Existing methods fail to generalize well across these scan-wise variations. Our goa...

Digital Resources for Traversing the Landscape of Human Aging: Databases, Key Computational Strategies, and Artificial Intelligence.

By 2050, nearly 20% of the global population will exceed 60 years old, experiencing compromised physiological and functional abilities, neurological disorders, and sarcopenia. Geroscience has evolved immensely through OMICS approaches and high-throughput technologies, generating massive datasets requiring efficient management, annotation, and storage. This highlights the need for user-friendly dat...

Prevalence and a LASSO-derived prediction model for screening-positive mild cognitive impairment among older adults in Wuhan.

This study aimed to investigate the prevalence of screening-positive mild cognitive impairment (s-MCI) and to develop a parsimonious prediction model ...

Regional variability in the associations between social and health-related risk factors and memory across Europe.

Interventions targeting social and health-related risk factors are thought to reduce the risk of cognitive decline and dementia in older age. Despite ...

Measurement fidelity, not model complexity, governs individual cognitive trajectory prediction in Parkinson's disease.

Whether individual-level cognitive trajectories in Parkinson's disease are predictable remains unresolved. Here, we provide convergent evidence that m...

Association of Staphylococcus aureus bloodstream infection with 7-day incident delirium in critically Ill adults: a propensity-weighted competing risk analysis.

BACKGROUND: Delirium is a frequent manifestation of acute brain dysfunction in critically ill patients with bloodstream infections (BSI). While the as...

Home-based eye tracking for early autism screening: a scoping review of approaches, evidence, and implementation challenges.

BACKGROUND: Early identification of autism spectrum disorder (ASD) is essential for improving developmental outcomes but remains challenging due to di...

Quantitative sleep EEG identifies CSF core biomarker-related subgroups in Alzheimer's disease.

Early detection and biological characterization of Alzheimer's disease (AD) remain challenging, as current diagnostic approaches rely on invasive cere...

Cascaded Deep Learning enables multimodal brain PET spatial normalization and quantification for Alzheimer's disease.

Semi-quantitative positron emission tomography (PET) analysis, particularly Centiloid and CenTauRz scaling, is essential for Alzheimer's disease (AD) ...

Machine learning and deep learning for neurological disease analysis: A systematic review across five major disorders.

Artificial Intelligence (AI) has become integral to the research of neurological diseases due to the rapid expansion of neuroimaging, clinical, physio...

Integrated multi-omics and experimental validation reveal CSK and FBLN1 as key targets of stanozolol in accelerating atherosclerosis.

BACKGROUND: Stanozolol, a synthetic anabolic androgenic steroid (AAS) widely abused to enhance performance, has poorly defined toxicological mechanism...

Developing and Testing a Brief Mindfulness Just-in-Time Adaptive Intervention to Reduce Stress Among Caregivers of People With Dementia: Quasi-Experimental Study.

BACKGROUND: Dementia caregiving entails chronic, fluctuating stress with downstream risks to caregivers' mental health and quality of care. Mindfulnes...

Application of Focused Ultrasound in Alzheimer's Disease: A Bibliometric Analysis.

OBJECTIVE: This study uses bibliometric analysis and knowledge mapping methods to systematically explore the emerging research frontiers and developme...

Uncertainty-aware multi-path framework with dynamic arbitration for Alzheimer's disease MRI classification.

As a progressive neurodegenerative disorder, Alzheimer's disease (AD) requires early and accurate diagnosis to delay pathological progression and impr...

Targeting the intrinsically disordered AR-NTD through a machine learning-based enhanced sampling workflow.

Targeting the intrinsically disordered N-terminal domain of the androgen receptor (AR-NTD) represents a promising strategy to overcome resistance in p...

Multimodal neuroimaging-based deep learning framework for pattern analysis and early prediction of neurodegenerative diseases.

Neurodegenerative diseases, such as Mild Cognitive Impairment (MCI) and Alzheimer's, pose significant challenges due to their progressive nature and l...

VAV3 is associated with atherosclerosis and ox-LDL-induced endothelial dysfunctional remodeling.

BACKGROUND: Atherosclerosis is a major cause of ischemic stroke and is characterized by complex immune-metabolic dysregulation. VAV3, a Rho guanine nu...

Results of a new model of videotraining for patients and caregivers for peritoneal dialysis: food for (AI) thought?

BACKGROUND: In an attempt to overcome the space-time limitations of traditional training we used a new telemedicine home-training model (Videotraining...

Profiling cognition and brain metabolism in amyotrophic lateral sclerosis and frontotemporal dementia.

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are described as a disease continuum, given their shared clinical, genetic and p...

Synthesis of Amyloid Images Using a Generative Adversarial Network from 2-Dimensional 18F-FDG Images and Evaluation for Clinical Use.

The use of amyloid PET to assess patient suitability of disease-modifying drugs for Alzheimer disease is increasing. This study aimed to synthesize am...