AIMC Topic: Cognitive Dysfunction

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Independent Component Analysis-Support Vector Machine-Based Computer-Aided Diagnosis System for Alzheimer's with Visual Support.

International journal of neural systems
Computer-aided diagnosis (CAD) systems constitute a powerful tool for early diagnosis of Alzheimer's disease (AD), but limitations on interpretability and performance exist. In this work, a fully automatic CAD system based on supervised learning meth...

Classification of patients with MCI and AD from healthy controls using directed graph measures of resting-state fMRI.

Behavioural brain research
Brain network alterations in patients with Alzheimer's disease (AD) has been the subject of much investigation, but the biological mechanisms underlying these alterations remain poorly understood. Here, we aim to identify the changes in brain network...

A support vector machine-based method to identify mild cognitive impairment with multi-level characteristics of magnetic resonance imaging.

Neuroscience
Mild cognitive impairment (MCI) represents a transitional state between normal aging and Alzheimer's disease (AD). Non-invasive diagnostic methods are desirable to identify MCI for early therapeutic interventions. In this study, we proposed a support...

Temporally Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer's Disease.

IEEE transactions on bio-medical engineering
Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment. However, most existing sparse learning-based studies only adopt cross-s...

Ensembles of Deep Learning Architectures for the Early Diagnosis of the Alzheimer's Disease.

International journal of neural systems
Computer Aided Diagnosis (CAD) constitutes an important tool for the early diagnosis of Alzheimer's Disease (AD), which, in turn, allows the application of treatments that can be simpler and more likely to be effective. This paper explores the constr...

State-space model with deep learning for functional dynamics estimation in resting-state fMRI.

NeuroImage
Studies on resting-state functional Magnetic Resonance Imaging (rs-fMRI) have shown that different brain regions still actively interact with each other while a subject is at rest, and such functional interaction is not stationary but changes over ti...

Relationship Induced Multi-Template Learning for Diagnosis of Alzheimer's Disease and Mild Cognitive Impairment.

IEEE transactions on medical imaging
As shown in the literature, methods based on multiple templates usually achieve better performance, compared with those using only a single template for processing medical images. However, most existing multi-template based methods simply average or ...

CSF YKL-40 and pTau181 are related to different cerebral morphometric patterns in early AD.

Neurobiology of aging
Cerebrospinal fluid (CSF) concentrations of YKL-40 that serve as biomarker of neuroinflammation are known to be altered along the clinico-biological continuum of Alzheimer's disease (AD). The specific structural cerebral correlates of CSF YKL-40 were...

Graph-guided joint prediction of class label and clinical scores for the Alzheimer's disease.

Brain structure & function
Accurate diagnosis of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment, is very important for early treatment. Over the last decade, various machine learning methods have been proposed to predict disease status and clinica...

Effects on Symptoms of Agitation and Depression in Persons With Dementia Participating in Robot-Assisted Activity: A Cluster-Randomized Controlled Trial.

Journal of the American Medical Directors Association
OBJECTIVES: To examine effects on symptoms of agitation and depression in nursing home residents with moderate to severe dementia participating in a robot-assisted group activity with the robot seal Paro.