Dementia

Volumetric Histogram-Based Alzheimer's Disease Detection Using Support Vector Machine.

In this research work, machine learning techniques are used to classify magnetic resonance imaging brain scans of people with Alzheimer's disease. This work deals with binary classification between Alzheimer's disease and cognitively normal. Supervised learning algorithms were used to train classifiers in which the accuracies are being compared. The database used is from The Alzheimer's Disease Ne...

Alzheimer's Disease Classification Based on Multi-feature Fusion.

BACKGROUND: In this study, we investigated the fusion of texture and morphometric features as a possible diagnostic biomarker for Alzheimer's Disease (AD).

Deep Learning for Alzheimer's Disease Classification using Texture Features.

BACKGROUND: We propose a classification method for Alzheimer's disease (AD) based on the texture of the hippocampus, which is the organ that is most a...

Social Robots as a Complementary Therapy in Chronic, Progressive Diseases.

Globally, the world population is ageing, which increases the prevalence of non-communicable diseases that affect patients both physically and psychol...

Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.

Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and fun...

[Big data and artificial intelligence for diagnostic decision support in atypical dementia].

The differential diagnosis of atypical dementia remains difficult. The use of positron emission tomography (PET) still represents the gold standard fo...

Detection of Early Stage Alzheimer's Disease using EEG Relative Power with Deep Neural Network.

Electroencephalogram (EEG) signal based early diagnosis of Alzheimer's Disease (AD), especially a discrimination between healthy control (HC) and mild...

Isometry Invariant Shape Descriptors for Abnormality Detection on Brain Surfaces Affected by Alzheimer's Disease.

Alzheimer's disease (AD), a progressive brain disorder, is the most common neurodegenerative disease in older adults. There is a need for brain struct...

A Clinically-Translatable Machine Learning Algorithm for the Prediction of Alzheimer's Disease Conversion in Individuals with Mild and Premild Cognitive Impairment.

BACKGROUND: Available therapies for Alzheimer's disease (AD) can only alleviate and delay the advance of symptoms, with the greatest impact eventually...

Network pharmacology-based analysis of Chinese herbal Naodesheng formula for application to Alzheimer's disease.

Naodesheng (NDS) formula, which consists of Rhizoma Chuanxiong, Lobed Kudzuvine, Carthamus tinctorius, Radix Notoginseng, and Crataegus pinnatifida, i...

Data Mining and Machine Learning Methods for Dementia Research.

Patient data in clinical research often includes large amounts of structured information, such as neuroimaging data, neuropsychological test results, ...

Development of Teaching Materials of Dementia by Incorporating a Communications Robot for Schoolchildren Who Are Dementia Supporters.

In this study, we aimed to teach elementary school students how to practically deal with elderly people with dementia and developed and evaluated teac...

Machine Learning, Sentiment Analysis, and Tweets: An Examination of Alzheimer's Disease Stigma on Twitter.

OBJECTIVES: Social scientists need practical methods for harnessing large, publicly available datasets that inform the social context of aging. We des...

Adding navigation, artificial audition and vital sign monitoring capabilities to a telepresence mobile robot for remote home care applications.

A telepresence mobile robot is a remote-controlled, wheeled device with wireless internet connectivity for bidirectional audio, video and data transmi...

Simulation-based design for robotic care device: Optimizing trajectory of transfer support robot.

This paper presents a framework of simulation-based design for robotic care devices developed to reduce the burden of caregiver and care receivers. Fi...

Modelling engagement in dementia through behaviour. Contribution for socially interactive robotics.

In this paper, we present a novel tool to measure engagement in people with dementia playing board games and interacting with a social robot, Pleo. We...

Further Development of a Robotic-Assisted Transfer Device.

The task of performing transfers, such as from a wheelchair to a bed, has a high risk of injury to both the caregiver and the person being transferre...

The Utilization of Robotic Pets in Dementia Care.

BACKGROUND: Behavioral problems may affect individuals with dementia, increasing the cost and burden of care. Pet therapy has been known to be emotion...

Development of a Late-Life Dementia Prediction Index with Supervised Machine Learning in the Population-Based CAIDE Study.

BACKGROUND AND OBJECTIVE: This study aimed to develop a late-life dementia prediction model using a novel validated supervised machine learning method...

Machine Learning and Molecular Dynamics Based Insights into Mode of Actions of Insulin Degrading Enzyme Modulators.

BACKGROUND: Alzheimer's disease (AD) is one of the most common lethal neurodegenerative disorders having impact on the lives of millions of people wor...