Alzheimer's Disease

A hybrid CNN-GCN framework for interpretable Alzheimer's disease diagnosis from MRI scans.

Medical image analysis for Alzheimer's Disease (AD) diagnosis faces two key challenges: capturing spatial dependencies between anatomically connected brain regions and providing clinically interpretable explanations. While Convolutional Neural Networks (CNNs) excel at local feature extraction and Vision Transformers handle long-range dependencies, neither explicitly models the relational structure...

Quality of Responses Generated by Artificial Intelligence Chatbots for Frequently Asked Questions by Caregivers of Presurgical Nasoalveolar Molding Therapy.

ObjectiveThe study compared the quality of responses generated by three artificial intelligence chatbots (AICs) for frequently asked questions (FAQs) by caregivers of presurgical nasoalveolar molding (PNAM) therapy.Material and MethodsTwenty-three FAQs on PNAM were posed to WhatsApp Meta AI (Llama 4), ChatGPT-4o, and Gemini 2.5 Flash, under the same conditions. Their responses were evaluated and c...

Comparing Stakeholders' Perspectives on Parkinson Disease Management and Digital Technologies: Exploratory International Survey.

BACKGROUND: Parkinson disease (PD) is a progressive neurodegenerative disorder that poses complex challenges for persons with PD, informal caregivers,...

Re: Clarifying comparative claims in digital cognitive assessment: Assessing concurrent validity in a shared cohort.

In response to correspondence from Cognivue, Inc. regarding our publication (Jannati et al., 2025), we clarify that our analysis employed a rigorous p...

Clarifying comparative claims in digital cognitive assessment: a matters arising on multimodal detection of cognitive impairment and amyloid positivity.

Digital cognitive assessments represent an important and rapidly evolving approach to detecting cognitive impairment and Alzheimer's disease-related p...

"There's not one part of the programme that hasn't been useful in my clinical practice": undergraduate nursing students' views and experiences of a Dementia Education Program.

Preparing nursing students to provide high-quality, person-centered dementia care is a global priority, yet most research has focused on measuring edu...

Determinants of Medical Help-Seeking Behavior Following Case Finding of Early Cognitive Impairment: Semistructured Interview Study of Patients and Caregivers.

BACKGROUND: Timely medical follow-up after a diagnosis of cognitive impairment, such as mild cognitive impairment (MCI) or dementia, is imperative for...

Biomarkers in preclinical and early Alzheimer's disease in China: a scoping review.

This scoping review synthesizes evidence on fluid and neuroimaging biomarkers for preclinical and early Alzheimer's disease (AD)-including mild cognit...

A novel diagnosis method based on multimodal-aware bi-objective competitive mechanism for Alzheimer's disease.

Alzheimer's disease (AD) is one of the most prevalent neurodegenerative disorders. Recent statistical surveys and studies indicate that AD is poised t...

Robust transcriptomic signatures of Alzheimer's disease progression: validated explainable AI approach.

The lack of validated stage-specific biomarkers hampers the understanding of Alzheimer's disease (AD) progression and clinical translation. Current tr...

Exploring and Targeting the Connection of Iron and Copper Homeostasis to Neurodegenerative Diseases.

Iron (Fe) and copper (Cu) are vital micronutrients that regulate many critical physiological processes in the human body, with their homeostasis in th...

Multimodal Artificial Intelligence for Early Detection and Precision Management of Inflammatory and Infiltrative Cardiomyopathies.

BACKGROUND: Inflammatory and infiltrative cardiomyopathies, including cardiac sarcoidosis, transthyretin amyloidosis, and autoimmune myocarditis, are ...

Digital Sleep-Wake Cycle Metrics and Dementia Prediction in Older Adults.

IMPORTANCE: Disruptions in the sleep-wake cycle have been reported in the preclinical period of dementia; whether they contribute to dementia predicti...

Predicting categorical and continuous Alzheimer's disease outcomes from a single MRI scan.

Deep learning (DL) has shown success in predicting Alzheimer's disease (AD) diagnosis, yet continuous measures such as cognitive assessment remain cri...

Cardiac activity monitoring for the heart rate classification with enhanced BiLSTM model.

Cardiac activity monitoring is important for assessing cardiovascular status and supporting computational analysis of heart-rate pattern variations fr...

Explainable machine learning for predicting longitudinal dementia status: Establishing a leakage-free benchmark.

Dementia research often suffers from methodological pitfalls such as label-information and subject-information leakages. Leveraging the longitudinal O...

Formulaic and novel language dissociate in Alzheimer's clinical syndrome: evidence for the Dual-Process Model.

INTRODUCTION: Spontaneous speech is commonly disrupted in persons with Alzheimer's disease (AD) and/or Alzheimer's clinical syndrome (ACS). Importantl...

CXCL16 promotes macrophage-driven inflammation and vascular smooth muscle cell phenotypic switching during carotid plaque destabilization.

BACKGROUND: Carotid plaque instability is a major determinant of ischemic stroke and is characterized by heightened inflammation and structural remode...

Aging beyond diagnosis: the MRI brain age gap across disorders.

The brain age gap (BAG), the difference between magnetic resonance imaging-predicted brain age and chronological age, is a proposed marker of neurobio...

Synthetic materials trained tactile sensing enables quantitative perception of Young's modulus and Poisson's ratio.

Accurately perceiving object softness remains challenging for tactile sensors, as current approaches estimate Young's modulus from object deformation ...