Alzheimer's Disease

Early diagnosis of Alzheimer's disease through handwriting analysis and deep learning: A review.

Alzheimer's disease (AD) is one of the most prevalent neurodegenerative disorders worldwide, requiring early identification for timely intervention and to slow disease progression. However, existing diagnostic approaches, while effective at later stages, remain limited in detecting early-stage AD. Handwriting analysis has recently emerged as a non-invasive, cost-effective, and ecologically valid d...

An LC-MS-guided AI enabled serum molecule-interpretable SERS platform for exploratory metabolomic analysis in Alzheimer's disease.

Label-free surface-enhanced Raman spectroscopy (SERS) offers a promising avenue for rapid metabolic phenotyping in complex biofluids, yet its translational potential is hindered by the challenge of deconvoluting overlapping spectral contributions and identifying specific metabolite signatures. Herein, we report a liquid chromatography-mass spectrometry (LC-MS)-guided AI enabled serum molecule-inte...

Development of AI-assisted 3D-printed degradable hydrogel microneedles for transdermal delivery of progesterone-loaded solid lipid nanoparticles: a novel approach to slowing Alzheimer's disease progression.

Progesterone (PG) is used to slow the progression of neurodegenerative diseases, particularly Alzheimer's disease (AD) in postmenopausal women. Howeve...

The geographic digital divide among dementia caregivers in the U.S.: a cross-sectional study.

BACKGROUND: Digital health tools, particularly patient portals, can support caregiving, but there is limited understanding of how sociodemographic and...

Disproportionately Elevated Sulcal Index (DESI): An automatically driven index representing disproportionate subarachnoid space enlargement in brain MRI scans.

INTRODUCTION: Idiopathic normal pressure hydrocephalus (iNPH) is frequently underdiagnosed due to non-specific symptoms and the risks of invasive test...

Top five Alzheimer Disease trial eligibility criteria favor men compared to women in a clinic-based cohort.

BACKGROUND: Less women participate in Alzheimer Disease (AD) trials compared to their estimated representation in the global dementia population. OBJE...

Predicting first onset of suicide attempt among children with suicidal ideation or non-suicidal self-injury using machine learning: a prospective population-based cohort study.

While children with suicidal ideation or non-suicidal self-injury (NSSI) are at high risk of suicide, most do not attempt suicide. This study aims to ...

Osteoarthritis and dementia: contrasting disorders driven by mutual pathways of autophagy, mTOR, GLP-1, AMPK, wnt, and WISP1.

INTRODUCTION: Increased global lifespan is paralleled by a rise in non-communicable diseases with osteoarthritis and dementia, including Alzheimer's d...

Global Perspectives on CNS Drug Innovation: Achievements, Barriers, and Priorities for the Next Decade.

BACKGROUND: Over the past decade, neuropsychopharmacology has shifted from stagnation to momentum, with first-in-class mechanisms and biomarker-enable...

Integration of glymphatic system function and hippocampal radiomics for diagnosis and conversion prediction of Alzheimer's disease.

BACKGROUND: Glymphatic system (GS) function and hippocampal microstructural changes are promising imaging markers of Alzheimer's disease (AD). This st...

A multifeature machine learning and resting-state EEG study reveals differences in beta oscillation in late-life depression with or without mild cognitive impairment.

BACKGROUND: Late-life depression (LLD) often co-occurs with mild cognitive impairment (MCI), and patients with LLD and MCI (LLD-MCI) have an increased...

Combining EEG, event-related potentials, and MRI biomarkers for detection of mild cognitive impairment: A machine learning approach.

OBJECTIVE: Mild cognitive impairment (MCI) is an intermediary stage between typical cognitive aging and dementia. Identifying reliable biomarkers for ...

Large language models for deductive qualitative content analysis in dementia-focused embedded pragmatic clinical trials: A comparative methodological study.

INTRODUCTION: Thematic coding helps researchers characterize intervention implementation in embedded pragmatic clinical trials (ePCTs), particularly i...

AI chatbots in strabismus care: A multidomain expert evaluation of caregiver-facing information.

AimTo evaluate and compare the performance of five artificial intelligence (AI) chatbots-ChatGPT (OpenAI 4), Google Gemini, Grok (xAI), DeepSeek, and ...

Factors Associated with Respite Care Use Among Veteran Caregivers: A Machine Learning Analysis.

BACKGROUND AND OBJECTIVES: Respite care provides temporary relief to family caregivers yet remains underused, and the factors shaping its utilization ...

Testing Near-Field Radio-Frequency Sensors to Predict Respiratory Distress in Patients Living With Dementia: A Pilot Feasibility and Acceptability Study.

BackgroundPeople living with dementia (PLWD) with advanced illness are prone to respiratory distress yet often cannot self-report dyspnea, delaying re...

Robust disease prognosis via diagnostic knowledge preservation: A sequential learning approach.

Accurate disease prognosis is essential for patient care but is often hindered by the scarcity of longitudinal data. This study explores deep learning...

The presymptomatic and early manifestations of semantic dementia.

People with semantic dementia (SD) or semantic variant primary progressive aphasia typically present with marked atrophy of the anterior temporal lobe...

Single-molecule detection of amino acid phosphorylation using electron tunnelling currents: toward neurodegenerative disease diagnosis.

Protein phosphorylation is one of the most prevalent post-translational modifications regulating biological functions, and its dysregulation is closel...

Data-driven detection of lucid episodes in advanced dementia: Application of latent class analysis to observational data.

BackgroundLucid episodes (LEs) in advanced dementia are significant clinical events yet are challenging to investigate as they are characterized by a ...