Neurology

Dementia

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

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Visual deep learning of unprocessed neuroimaging characterises dementia subtypes and generalises across non-stereotypic samples.

BACKGROUND: Dementia's diagnostic protocols are mostly based on standardised neuroimaging data colle...

Natural language processing techniques for studying language in pathological ageing: A scoping review.

BACKGROUND: In the past few years there has been a growing interest in the employment of verbal prod...

HGM-cNet: Integrating hippocampal gray matter probability map into a cascaded deep learning framework improves hippocampus segmentation.

A robust cascaded deep learning framework with integrated hippocampal gray matter (HGM) probability ...

Deciphering multiple sclerosis disability with deep learning attention maps on clinical MRI.

The application of convolutional neural networks (CNNs) to MRI data has emerged as a promising appro...

Toward explainable AI-empowered cognitive health assessment.

Explainable artificial intelligence (XAI) is of paramount importance to various domains, including h...

Automatic Detection of Alzheimer's Disease using Deep Learning Models and Neuro-Imaging: Current Trends and Future Perspectives.

Deep learning algorithms have a huge influence on tackling research issues in the field of medical i...

Diagnosis of Alzheimer Disease and Tauopathies on Whole-Slide Histopathology Images Using a Weakly Supervised Deep Learning Algorithm.

Neuropathologic assessment during autopsy is the gold standard for diagnosing neurodegenerative diso...

Deep Learning-Based Feature Extraction with MRI Data in Neuroimaging Genetics for Alzheimer's Disease.

The prognosis and treatment of patients suffering from Alzheimer's disease (AD) have been among the ...

Ethical issues when using digital biomarkers and artificial intelligence for the early detection of dementia.

Dementia poses a growing challenge for health services but remains stigmatized and under-recognized....

Nurses' perception towards care robots and their work experience with socially assistive technology during COVID-19: A qualitative study.

This study aimed to explore nurses' perceptions towards care robots and their work experiences in ca...

Interpretable machine learning for dementia: A systematic review.

INTRODUCTION: Machine learning research into automated dementia diagnosis is becoming increasingly p...

Convolution Neural Networks and Self-Attention Learners for Alzheimer Dementia Diagnosis from Brain MRI.

Alzheimer's disease (AD) is the most common form of dementia. Computer-aided diagnosis (CAD) can hel...

Precise Discrimination for Multiple Etiologies of Dementia Cases Based on Deep Learning with Electroencephalography.

INTRODUCTION: It is critical to develop accurate and universally available biomarkers for dementia d...

[Artificial intelligence and ethics in healthcare-balancing act or symbiosis?].

Artificial intelligence (AI) is becoming increasingly important in healthcare. This development trig...

A machine-learning algorithm for predicting brain age using Rey-Osterrieth complex figure tests of healthy participants.

OBJECTIVE: Neuropsychologists widely use the Rey-Osterrieth complex figure test (RCFT) as part of ne...

Anatomically interpretable deep learning of brain age captures domain-specific cognitive impairment.

The gap between chronological age (CA) and biological brain age, as estimated from magnetic resonanc...

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