Dementia

Successful Resuscitation of a Young Girl Who Drank Rivastigmine With Respiratory Failure.

Rivastigmine is a non-competitive reversible inhibitor of acetylcholinesterase which is approved as ...

Application of Big Data and Artificial Intelligence technologies to dementia prevention research: an opportunity for low-and-middle-income countries.

[Early prognosis of Alzheimer's disease based on convolutional neural networks and ensemble learning].

Alzheimer's disease (AD) is a typical neurodegenerative disease, which is clinically manifested as a...

Multimodal Data Fusion of Deep Learning and Dynamic Functional Connectivity Features to Predict Alzheimer's Disease Progression.

Early prediction of diseased brain conditions is critical for curing illness and preventing irrevers...

Alzheimer's Disease Brain Network Classification Using Improved Transfer Feature Learning with Joint Distribution Adaptation.

Alzheimer's disease significantly affects the quality of life of patients. This paper proposes an ap...

[Support for Patients and Their Family Using Artificial Intelligence].

For patients with dementia and their family, artificial intelligence (AI) has been utilized to suppo...

[Use AI for Dementia Diagnosis].

Using AI for dementia diagnosis is still in research stage, however some of the work points to the d...

[Artificial Intelligence for Diagnostic Support of Neuroimage].

Artificial intelligence (AI) shows promises in terms of diagnostic support on neuroimaging. We devel...

Evaluation of a Companion Robot for Individuals With Dementia: Quantitative Findings of the MARIO Project in an Irish Residential Care Setting.

The current study focuses on the short-term effect of MARIO, a social robot, on quality of life, dep...

An artificial neural network model for clinical score prediction in Alzheimer disease using structural neuroimaging measures.

BACKGROUND: The development of diagnostic and prognostic tools for Alzheimer disease is complicated ...

The Residual Center of Mass: An Image Descriptor for the Diagnosis of Alzheimer Disease.

A crucial quest in neuroimaging is the discovery of image features (biomarkers) associated with neur...

Fused Group Lasso Regularized Multi-Task Feature Learning and Its Application to the Cognitive Performance Prediction of Alzheimer's Disease.

Alzheimer's disease (AD) is characterized by gradual neurodegeneration and loss of brain function, e...

"She Had a Smile on Her Face as Wide as the Great Australian Bite": A Qualitative Examination of Family Perceptions of a Therapeutic Robot and a Plush Toy.

BACKGROUND AND OBJECTIVES: Recent years have seen social robotic pets introduced as a means of treat...

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

Globally, the world population is ageing, which increases the prevalence of non-communicable disease...

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 ...

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

BACKGROUND: In this study, we investigated the fusion of texture and morphometric features as a poss...

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 b...

Screening for Alzheimer's Disease Using Saliva: A New Approach Based on Machine Learning and Raman Hyperspectroscopy.

BACKGROUND: Alzheimer's disease and related dementias (ADRDs) are being diagnosed at epidemic rates,...

Optimizing Machine Learning Methods to Improve Predictive Models of Alzheimer's Disease.

BACKGROUND: Predicting clinical course of cognitive decline can boost clinical trials' power and imp...

Improving PET Imaging Acquisition and Analysis With Machine Learning: A Narrative Review With Focus on Alzheimer's Disease and Oncology.

Machine learning (ML) algorithms have found increasing utility in the medical imaging field and nume...

Detecting Alzheimer's Disease from Continuous Speech Using Language Models.

BACKGROUND: Recently, many studies have been carried out to detect Alzheimer's disease (AD) from con...