Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer's disease, Parkinson's …
Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an
important role in understanding brain functionalities and its disorders during the last couple …
important role in understanding brain functionalities and its disorders during the last couple …
A review of the functional and anatomical default mode network in schizophrenia
Schizophrenia is a severe mental disorder characterized by impaired perception, delusions,
thought disorder, abnormal emotion regulation, altered motor function, and impaired drive …
thought disorder, abnormal emotion regulation, altered motor function, and impaired drive …
Multimodal neuroimaging feature learning with multimodal stacked deep polynomial networks for diagnosis of Alzheimer's disease
The accurate diagnosis of Alzheimer's disease (AD) and its early stage, ie, mild cognitive
impairment, is essential for timely treatment and possible delay of AD. Fusion of multimodal …
impairment, is essential for timely treatment and possible delay of AD. Fusion of multimodal …
[HTML][HTML] Information fusion and artificial intelligence for smart healthcare: a bibliometric study
With the fast progress in information technologies and artificial intelligence (AI), smart
healthcare has gained considerable momentum. By using advanced technologies like AI …
healthcare has gained considerable momentum. By using advanced technologies like AI …
A Hitchhiker's guide to functional magnetic resonance imaging
JM Soares, R Magalhães, PS Moreira… - Frontiers in …, 2016 - frontiersin.org
Functional Magnetic Resonance Imaging (fMRI) studies have become increasingly popular
both with clinicians and researchers as they are capable of providing unique insights into …
both with clinicians and researchers as they are capable of providing unique insights into …
Towards a brain‐based predictome of mental illness
Neuroimaging‐based approaches have been extensively applied to study mental illness in
recent years and have deepened our understanding of both cognitively healthy and …
recent years and have deepened our understanding of both cognitively healthy and …
A brain-inspired trust management model to assure security in a cloud based IoT framework for neuroscience applications
Rapid advancement of Internet of Things (IoT) and cloud computing enables neuroscientists
to collect multilevel and multichannel brain data to better understand brain functions …
to collect multilevel and multichannel brain data to better understand brain functions …
QLBP: Dynamic patterns-based feature extraction functions for automatic detection of mental health and cognitive conditions using EEG signals
Background Severe psychiatric disorders, including depressive disorders, schizophrenia
spectrum disorders, and intellectual disability, have devastating impacts on vital life domains …
spectrum disorders, and intellectual disability, have devastating impacts on vital life domains …
Structural neuroimaging of anorexia nervosa: future directions in the quest for mechanisms underlying dynamic alterations
Anorexia nervosa (AN) is a serious eating disorder characterized by self-starvation and
extreme weight loss. Pseudoatrophic brain changes are often readily visible in individual …
extreme weight loss. Pseudoatrophic brain changes are often readily visible in individual …
A survey of deep learning for alzheimer's disease
Alzheimer's and related diseases are significant health issues of this era. The
interdisciplinary use of deep learning in this field has shown great promise and gathered …
interdisciplinary use of deep learning in this field has shown great promise and gathered …