Dementia

Deep learning signature of brain [F]FDG PET associated with cognitive outcome of rapid eye movement sleep behavior disorder.

An objective biomarker to predict the outcome of isolated rapid eye movement sleep behavior disorder...

Multi-label classification of Alzheimer's disease stages from resting-state fMRI-based correlation connectivity data and deep learning.

Alzheimer's disease is a neurodegenerative condition that gradually impairs cognitive abilities. Rec...

Strategies to Implement Pet Robots in Long-Term Care Facilities for Dementia Care: A Modified Delphi Study.

OBJECTIVES: Pet robots are technology-based substitutes for live animals that have demonstrated psyc...

Early diagnosis of Alzheimer's disease and mild cognitive impairment based on electroencephalography: From the perspective of event related potentials and deep learning.

Alzheimer's disease (AD), a neurodegenerative disorder characterized by progressive cognitive declin...

Deep learning-based diagnosis of Alzheimer's disease using brain magnetic resonance images: an empirical study.

The limited accessibility of medical specialists for Alzheimer's disease (AD) can make obtaining an ...

Brain Age Prediction/Classification through Recurrent Deep Learning with Electroencephalogram Recordings of Seizure Subjects.

With modern population growth and an increase in the average lifespan, more patients are becoming af...

Functional magnetic resonance imaging, deep learning, and Alzheimer's disease: A systematic review.

Alzheimer's disease (AD) is currently diagnosed using a mixture of psychological tests and clinical ...

Identifying the presence and severity of dementia by applying interpretable machine learning techniques on structured clinical records.

BACKGROUND: Dementia develops as cognitive abilities deteriorate, and early detection is critical fo...

Generalizable deep learning model for early Alzheimer's disease detection from structural MRIs.

Early diagnosis of Alzheimer's disease plays a pivotal role in patient care and clinical trials. In ...

Social Robotics and Dementia: Results from the eWare Project in Supporting Older People and Their Informal Caregivers.

The aim of this paper is to describe the results collected with the Italian study conducted within e...

A Care Robot with Ethical Sensing System for Older Adults at Home.

Many studies have explored emotional and mental services that robots can provide for older adults, s...

A deep learning model for detection of Alzheimer's disease based on retinal photographs: a retrospective, multicentre case-control study.

BACKGROUND: There is no simple model to screen for Alzheimer's disease, partly because the diagnosis...

Artificial intelligence for detection of Alzheimer's disease: demonstration of real-world value is required to bridge the translational gap.

Adera2.0: A Drug Repurposing Workflow for Neuroimmunological Investigations Using Neural Networks.

Drug repurposing in the context of neuroimmunological (NI) investigations is still in its primary st...

Development of a deep learning network for Alzheimer's disease classification with evaluation of imaging modality and longitudinal data.

. Neuroimaging uncovers important information about disease in the brain. Yet in Alzheimer's disease...

Circulating serum metabolites as predictors of dementia: a machine learning approach in a 21-year follow-up of the Whitehall II cohort study.

BACKGROUND: Age is the strongest risk factor for dementia and there is considerable interest in iden...

Imaging of the optic nerve: technological advances and future prospects.

Over the past decade, ocular imaging strategies have greatly advanced the diagnosis and follow-up of...

Artificial intelligence (AI) for home support interventions in dementia: a scoping review protocol.

INTRODUCTION: Dementia has become one of the significant causes of disability and dependency among o...

Interpretable deep learning of myelin histopathology in age-related cognitive impairment.

Age-related cognitive impairment is multifactorial, with numerous underlying and frequently co-morbi...

A Hierarchical Ensemble Deep Learning Activity Recognition Approach with Wearable Sensors Based on Focal Loss.

Abnormal activity in daily life is a relatively common symptom of chronic diseases, such as dementia...

Predicting conversion to Alzheimer's disease in individuals with Mild Cognitive Impairment using clinically transferable features.

Patients with Mild Cognitive Impairment (MCI) have an increased risk of Alzheimer's disease (AD). Ea...