AIMC Topic: Brain

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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...

Longitudinal clinical score prediction in Alzheimer's disease with soft-split sparse regression based random forest.

Neurobiology of aging
Alzheimer's disease (AD) is an irreversible neurodegenerative disease and affects a large population in the world. Cognitive scores at multiple time points can be reliably used to evaluate the progression of the disease clinically. In recent studies,...

Atypical Asymmetry for Processing Human and Robot Faces in Autism Revealed by fNIRS.

PloS one
Deficits in the visual processing of faces in autism spectrum disorder (ASD) individuals may be due to atypical brain organization and function. Studies assessing asymmetric brain function in ASD individuals have suggested that facial processing, whi...

Assessing the user experience of older adults using a neural network trained to recognize emotions from brain signals.

Journal of biomedical informatics
The use of Ambient Assisted Living (AAL) technologies as a means to cope with problems that arise due to an increasing and aging population is becoming usual. AAL technologies are used to prevent, cure and improve the wellness and health conditions o...

Dynamic regulation of RNA editing in human brain development and disease.

Nature neuroscience
RNA editing is increasingly recognized as a molecular mechanism regulating RNA activity and recoding proteins. Here we surveyed the global landscape of RNA editing in human brain tissues and identified three unique patterns of A-to-I RNA editing rate...

Growing Homophilic Networks Are Natural Navigable Small Worlds.

PloS one
Navigability, an ability to find a logarithmically short path between elements using only local information, is one of the most fascinating properties of real-life networks. However, the exact mechanism responsible for the formation of navigation pro...

A multiple hold-out framework for Sparse Partial Least Squares.

Journal of neuroscience methods
BACKGROUND: Supervised classification machine learning algorithms may have limitations when studying brain diseases with heterogeneous populations, as the labels might be unreliable. More exploratory approaches, such as Sparse Partial Least Squares (...

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...

Predict or classify: The deceptive role of time-locking in brain signal classification.

Scientific reports
Several experimental studies claim to be able to predict the outcome of simple decisions from brain signals measured before subjects are aware of their decision. Often, these studies use multivariate pattern recognition methods with the underlying as...