Dementia

Modeling autosomal dominant Alzheimer's disease with machine learning.

INTRODUCTION: Machine learning models were used to discover novel disease trajectories for autosomal...

Frontotemporal EEG to guide sedation in COVID-19 related acute respiratory distress syndrome.

OBJECTIVE: To study if limited frontotemporal electroencephalogram (EEG) can guide sedation changes ...

Modular machine learning for Alzheimer's disease classification from retinal vasculature.

Alzheimer's disease is the leading cause of dementia. The long progression period in Alzheimer's dis...

Comments on Pu et al. (2021), "The effect of a social robot intervention on sleep and motor activity of people living with dementia and chronic pain: A pilot randomized controlled trial".

Computer-Aided Diagnosis of Alzheimer's Disease through Weak Supervision Deep Learning Framework with Attention Mechanism.

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease causing dementia and poses ...

Deep learning detection of informative features in tau PET for Alzheimer's disease classification.

BACKGROUND: Alzheimer's disease (AD) is the most common type of dementia, typically characterized by...

Fused Sparse Network Learning for Longitudinal Analysis of Mild Cognitive Impairment.

Alzheimer's disease (AD) is a neurodegenerative disease with an irreversible and progressive process...

Identification of Alzheimer's disease using a convolutional neural network model based on T1-weighted magnetic resonance imaging.

The classification of Alzheimer's disease (AD) using deep learning methods has shown promising resul...

EEG-Based Emotion Classification for Alzheimer's Disease Patients Using Conventional Machine Learning and Recurrent Neural Network Models.

As the number of patients with Alzheimer's disease (AD) increases, the effort needed to care for the...

Transfer learning for predicting conversion from mild cognitive impairment to dementia of Alzheimer's type based on a three-dimensional convolutional neural network.

Dementia of Alzheimer's type (DAT) is associated with devastating and irreversible cognitive decline...

Simultaneously Detecting Monoamine Oxidase A and B in Disease Cell/Tissue Samples Using Paper-Based Devices.

As enzymes in the outer membrane of the mitochondrion, monoamine oxidases (MAOs) can catalyze the ox...

Digital Gaming Interventions in Psychiatry: Evidence, Applications and Challenges.

Human evolution has regularly intersected with technology. Digitalization of various services has br...

A comparison of machine learning methods for survival analysis of high-dimensional clinical data for dementia prediction.

Data collected from clinical trials and cohort studies, such as dementia studies, are often high-dim...

The effect of PARO robotic seals for hospitalized patients with dementia: A feasibility study.

Robotic seals have been studied in long-term care settings; though, no studies of patients with deme...

The Perceptions of People with Dementia and Key Stakeholders Regarding the Use and Impact of the Social Robot MARIO.

People with dementia often experience loneliness and social isolation. This can result in increased ...

Identification of early mild cognitive impairment using multi-modal data and graph convolutional networks.

BACKGROUND: The identification of early mild cognitive impairment (EMCI), which is an early stage of...

Use of Patient-Reported Symptoms from an Online Symptom Tracking Tool for Dementia Severity Staging: Development and Validation of a Machine Learning Approach.

BACKGROUND: SymptomGuide Dementia (DGI Clinical Inc) is a publicly available online symptom tracking...

Development and Validation of a Deep Learning-Based Automatic Brain Segmentation and Classification Algorithm for Alzheimer Disease Using 3D T1-Weighted Volumetric Images.

BACKGROUND AND PURPOSE: Limited evidence has suggested that a deep learning automatic brain segmenta...

Alzheimer's diagnosis using deep learning in segmenting and classifying 3D brain MR images.

BACKGROUND AND OBJECTIVES: Dementia is one of the brain diseases with serious symptoms such as memor...

Internet of Things and Machine Learning for Healthy Ageing: Identifying the Early Signs of Dementia.

Identifying the symptoms of the early stages of dementia is a difficult task, particularly for older...

Testing a convolutional neural network-based hippocampal segmentation method in a stroke population.

As stroke mortality rates decrease, there has been a surge of effort to study poststroke dementia (P...