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Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review
Autism spectrum disorder (ASD) is a brain condition characterized by diverse signs and
symptoms that appear in early childhood. ASD is also associated with communication …
symptoms that appear in early childhood. ASD is also associated with communication …
Salience processing and insular cortical function and dysfunction
The brain is constantly bombarded by stimuli, and the relative salience of these inputs
determines which are more likely to capture attention. A brain system known as the'salience …
determines which are more likely to capture attention. A brain system known as the'salience …
[PDF][PDF] Explanations based on the missing: Towards contrastive explanations with pertinent negatives
In this paper we propose a novel method that provides contrastive explanations justifying the
classification of an input by a black box classifier such as a deep neural network. Given an …
classification of an input by a black box classifier such as a deep neural network. Given an …
MS-Net: multi-site network for improving prostate segmentation with heterogeneous MRI data
Automated prostate segmentation in MRI is highly demanded for computer-assisted
diagnosis. Recently, a variety of deep learning methods have achieved remarkable progress …
diagnosis. Recently, a variety of deep learning methods have achieved remarkable progress …
[HTML][HTML] Identification of autism spectrum disorder using deep learning and the ABIDE dataset
The goal of the present study was to apply deep learning algorithms to identify autism
spectrum disorder (ASD) patients from large brain imaging dataset, based solely on the …
spectrum disorder (ASD) patients from large brain imaging dataset, based solely on the …
Resting-state connectivity biomarkers define neurophysiological subtypes of depression
Biomarkers have transformed modern medicine but remain largely elusive in psychiatry,
partly because there is a weak correspondence between diagnostic labels and their …
partly because there is a weak correspondence between diagnostic labels and their …
ASD-DiagNet: a hybrid learning approach for detection of autism spectrum disorder using fMRI data
Heterogeneous mental disorders such as Autism Spectrum Disorder (ASD) are notoriously
difficult to diagnose, especially in children. The current psychiatric diagnostic process is …
difficult to diagnose, especially in children. The current psychiatric diagnostic process is …
Enhancing studies of the connectome in autism using the autism brain imaging data exchange II
The second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance
the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent …
the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent …
Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example
Abstract Resting-state functional Magnetic Resonance Imaging (R-fMRI) holds the promise
to reveal functional biomarkers of neuropsychiatric disorders. However, extracting such …
to reveal functional biomarkers of neuropsychiatric disorders. However, extracting such …
Automated detection of autism spectrum disorder using a convolutional neural network
Background: Convolutional neural networks (CNN) have enabled significant progress in
speech recognition, image classification, automotive software engineering, and …
speech recognition, image classification, automotive software engineering, and …