Neurology

Dementia

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

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Diagnosis of Dementia by Machine learning methods in Epidemiological studies: a pilot exploratory study from south India.

BACKGROUND: There are limited data on the use of artificial intelligence methods for the diagnosis o...

Identifying incipient dementia individuals using machine learning and amyloid imaging.

Identifying individuals destined to develop Alzheimer's dementia within time frames acceptable for c...

Machine learning and microsimulation techniques on the prognosis of dementia: A systematic literature review.

BACKGROUND: Dementia is a complex disorder characterized by poor outcomes for the patients and high ...

A Pilot Randomized Trial of a Companion Robot for People With Dementia Living in the Community.

OBJECTIVES: To investigate the affective, social, behavioral, and physiological effects of the compa...

Diagnosis of Alzheimer's Disease Using Dual-Tree Complex Wavelet Transform, PCA, and Feed-Forward Neural Network.

. Error-free diagnosis of Alzheimer's disease (AD) from healthy control (HC) patients at an early st...

Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing.

Developing effective and affordable biomarkers for dementias is critical given the difficulty to ach...

Diagnosis of Alzheimer's Disease Based on Structural MRI Images Using a Regularized Extreme Learning Machine and PCA Features.

Alzheimer's disease (AD) is a progressive, neurodegenerative brain disorder that attacks neurotransm...

Feature selective temporal prediction of Alzheimer's disease progression using hippocampus surface morphometry.

INTRODUCTION: Prediction of Alzheimer's disease (AD) progression based on baseline measures allows u...

Low-Cost Robotic Assessment of Visuo-Motor Deficits in Alzheimer's Disease.

A low-cost robotic interface was used to assess the visuo-motor performance of patients with Alzheim...

Quad-phased data mining modeling for dementia diagnosis.

BACKGROUND: The number of people with dementia is increasing along with people's ageing trend worldw...

A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages.

Neuroimaging has made it possible to measure pathological brain changes associated with Alzheimer's ...

Automated detection of pathologic white matter alterations in Alzheimer's disease using combined diffusivity and kurtosis method.

Diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) are important diffusion MRI tech...

Protective effect of Nelumbo nucifera extracts on beta amyloid protein induced apoptosis in PC12 cells, in vitro model of Alzheimer's disease.

Alzheimer's disease (AD) is the most common cause of dementia in the elderly. β-Amyloid (Aβ) has bee...

Mimicking Neurotransmitter Release in Chemical Synapses via Hysteresis Engineering in MoS Transistors.

Neurotransmitter release in chemical synapses is fundamental to diverse brain functions such as moto...

Early identification of mild cognitive impairment using incomplete random forest-robust support vector machine and FDG-PET imaging.

Alzheimer's disease (AD) is the most common type of dementia and will be an increasing health proble...

Predicting primary progressive aphasias with support vector machine approaches in structural MRI data.

Primary progressive aphasia (PPA) encompasses the three subtypes nonfluent/agrammatic variant PPA, s...

Optimizing Neuropsychological Assessments for Cognitive, Behavioral, and Functional Impairment Classification: A Machine Learning Study.

Subjects with Alzheimer's disease (AD) show loss of cognitive functions and change in behavioral and...

Deep ensemble learning of sparse regression models for brain disease diagnosis.

Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in ...

Relational-Regularized Discriminative Sparse Learning for Alzheimer's Disease Diagnosis.

Accurate identification and understanding informative feature is important for early Alzheimer's dis...

Predicting probable Alzheimer's disease using linguistic deficits and biomarkers.

BACKGROUND: The manual diagnosis of neurodegenerative disorders such as Alzheimer's disease (AD) and...

A natural language-based presentation of cognitive stimulation to people with dementia in assistive technology: A pilot study.

Currently, an estimated 36 million people worldwide are affected by Alzheimer's disease or related d...

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