Neurology

Dementia

Latest AI and machine learning research in dementia for healthcare professionals.

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Stacked autoencoders as new models for an accurate Alzheimer's disease classification support using resting-state EEG and MRI measurements.

OBJECTIVE: This retrospective and exploratory study tested the accuracy of artificial neural network...

Automated detection of cerebral microbleeds in MR images: A two-stage deep learning approach.

Cerebral Microbleeds (CMBs) are small chronic brain hemorrhages, which have been considered as diagn...

Prediction of 7-year's conversion from subjective cognitive decline to mild cognitive impairment.

Subjective cognitive decline (SCD) is a high-risk yet less understood status before developing Alzhe...

Detection of Mild Cognitive Impairment Through Natural Language and Touchscreen Typing Processing.

Mild cognitive impairment (MCI), an identified prodromal stage of Alzheimer's Disease (AD), often ev...

A Comparative Analysis of Hybrid Deep Learning Models for Human Activity Recognition.

Recent advances in artificial intelligence and machine learning (ML) led to effective methods and to...

Formal caregivers' perceptions and experiences of using pet robots for persons living with dementia in long-term care: A meta-ethnography.

AIM: To explore the formal caregivers' perceptions and experiences of using pet robots for persons l...

Effects on sleep from group activity with a robotic seal for nursing home residents with dementia: a cluster randomized controlled trial.

OBJECTIVES: Sleep disturbances are common in people with dementia and increase with the severity of ...

Classifications of Neurodegenerative Disorders Using a Multiplex Blood Biomarkers-Based Machine Learning Model.

Easily accessible biomarkers for Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal ...

Influence of medical domain knowledge on deep learning for Alzheimer's disease prediction.

BACKGROUND AND OBJECTIVE: Alzheimer's disease (AD) is the most common type of dementia that can seri...

Multifactorial 10-Year Prior Diagnosis Prediction Model of Dementia.

Dementia is a neurodegenerative disorder that affects the older adult population. To date, no cure o...

Artificial Intelligence and Machine Learning in Nuclear Medicine: Future Perspectives.

Artificial intelligence and machine learning based approaches are increasingly finding their way int...

Multi-slice representational learning of convolutional neural network for Alzheimer's disease classification using positron emission tomography.

BACKGROUND: Alzheimer's Disease (AD) is a degenerative brain disorder that often occurs in people ov...

Disentangling time series between brain tissues improves fMRI data quality using a time-dependent deep neural network.

Functional MRI (fMRI) is a prominent imaging technique to probe brain function, however, a substanti...

Predicting the progression of mild cognitive impairment to Alzheimer's disease by longitudinal magnetic resonance imaging-based dictionary learning.

OBJECTIVE: Efficient prediction of the progression of mild cognitive impairment (MCI) to Alzheimer's...

Caregiver burden in stroke inpatients: a randomized study comparing robot-assisted gait training and conventional therapy.

The effects of caregiver burden during the inpatient rehabilitation period have not yet been investi...

Monitoring behavioral symptoms of dementia using activity trackers.

Tertiary disease prevention for dementia focuses on improving the quality of life of the patient. Th...

VEPAD - Predicting the effect of variants associated with Alzheimer's disease using machine learning.

INTRODUCTION: Alzheimer's disease (AD) is a complex and heterogeneous disease that affects neuronal ...

Predicting Alzheimer's disease progression using deep recurrent neural networks.

Early identification of individuals at risk of developing Alzheimer's disease (AD) dementia is impor...

AI-driven attenuation correction for brain PET/MRI: Clinical evaluation of a dementia cohort and importance of the training group size.

INTRODUCTION: Robust and reliable attenuation correction (AC) is a prerequisite for accurate quantif...

Changes in technology acceptance among older people with dementia: the role of social robot engagement.

OBJECTIVE: Emerging technologies such as social robots have shown to be effective in reducing loneli...

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