AIMC Topic: Alzheimer Disease

Clear Filters Showing 1 to 10 of 1008 articles

A smart secure virtual reality immersive application for alzheimer's and dementia patients.

Scientific reports
Alzheimer's disease (AD) poses significant challenges for the elderly, leading to cognitive decline, social isolation, and lower quality of life. Current interventions often require cumbersome wearable devices e.g. the camera-based monitoring that ma...

Non-genetic neuromodulation with graphene optoelectronic actuators for disease models, stem cell maturation, and biohybrid robotics.

Nature communications
Light can serve as a tunable trigger for neurobioengineering technologies, enabling probing, control, and enhancement of brain function with unmatched spatiotemporal precision. Yet, these technologies often require genetic or structural alterations o...

Optimizing timing and cost-effective use of plasma biomarkers in Alzheimer's disease.

Alzheimer's research & therapy
BACKGROUND AND OBJECTIVES: Early and cost-effective identification of amyloid positivity is crucial for Alzheimer's disease (AD) diagnosis. While amyloid PET is the gold standard, plasma biomarkers such as phosphorylated tau 217 (pTau217) provide a p...

AI-driven fusion of multimodal data for Alzheimer's disease biomarker assessment.

Nature communications
Alzheimer's disease (AD) diagnosis hinges on detecting amyloid beta (Aβ) plaques and neurofibrillary tau (τ) tangles, typically assessed using PET imaging. While accurate, these modalities are expensive and not widely accessible, limiting their utili...

Improving early detection of Alzheimer's disease through MRI slice selection and deep learning techniques.

Scientific reports
Alzheimer's disease is a progressive neurodegenerative disorder marked by cognitive decline, memory loss, and behavioral changes. Early diagnosis, particularly identifying Early Mild Cognitive Impairment (EMCI), is vital for managing the disease and ...

Multimodal Alzheimer's disease recognition from image, text and audio.

Scientific reports
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that significantly affects cognitive function. One widely used diagnostic approach involves analyzing patients' verbal descriptions of pictures. While prior studies have primarily f...

Longitudinal structural MRI-based deep learning and radiomics features for predicting Alzheimer's disease progression.

Alzheimer's research & therapy
BACKGROUND: Alzheimer's disease (AD) is the principal cause of dementia and requires the early diagnosis of people with mild cognitive impairment (MCI) who are at high risk of progressing. Early diagnosis is imperative for optimizing clinical managem...

Developing an Equitable Machine Learning-Based Music Intervention for Older Adults At Risk for Alzheimer Disease: Protocol for Algorithm Development and Validation.

JMIR research protocols
BACKGROUND: Given the high prevalence and cost of Alzheimer disease (AD), it is crucial to develop equitable interventions to address lifestyle factors associated with AD incidence (eg, depression). While lifestyle interventions show promise for redu...

Alzheimer's disease risk prediction using machine learning for survival analysis with a comorbidity-based approach.

Scientific reports
Alzheimer's disease (AD) presents a pressing global health challenge, demanding improved strategies for early detection and understanding its progression. In this study, we address this need by employing survival analysis techniques to predict transi...

VR-based gamma sensory stimulation: a pilot feasibility study.

Scientific reports
Alzheimer's disease (AD) presents a critical global health challenge, with current therapies offering limited efficacy and safety in halting disease progression. Gamma sensory stimulation (GSS) has emerged as a promising non-invasive neuromodulation ...