rs-fMRI and machine learning for ASD diagnosis: a systematic review and meta-analysis
Abstract Autism Spectrum Disorder (ASD) diagnosis is still based on behavioral criteria
through a lengthy and time-consuming process. Much effort is being made to identify brain …
through a lengthy and time-consuming process. Much effort is being made to identify brain …
A brief review on multi-task learning
KH Thung, CY Wee - Multimedia Tools and Applications, 2018 - Springer
Abstract Multi-task learning (MTL), which optimizes multiple related learning tasks at the
same time, has been widely used in various applications, including natural language …
same time, has been widely used in various applications, including natural language …
Identifying autism spectrum disorder with multi-site fMRI via low-rank domain adaptation
Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is characterized by a
wide range of symptoms. Identifying biomarkers for accurate diagnosis is crucial for early …
wide range of symptoms. Identifying biomarkers for accurate diagnosis is crucial for early …
Resting-state functional MRI studies on infant brains: a decade of gap-filling efforts
Resting-state functional MRI (rs-fMRI) is one of the most prevalent brain functional imaging
modalities. Previous rs-fMRI studies have mainly focused on adults and elderly subjects …
modalities. Previous rs-fMRI studies have mainly focused on adults and elderly subjects …
Transient states of network connectivity are atypical in autism: A dynamic functional connectivity study
There is ample evidence of atypical functional connectivity (FC) in autism spectrum
disorders (ASDs). However, transient relationships between neural networks cannot be …
disorders (ASDs). However, transient relationships between neural networks cannot be …
Unsupervised manifold learning using high-order morphological brain networks derived from T1-w MRI for autism diagnosis
M Soussia, I Rekik - Frontiers in neuroinformatics, 2018 - frontiersin.org
Brain disorders, such as Autism Spectrum Disorder (ASD), alter brain functional (from fMRI)
and structural (from diffusion MRI) connectivities at multiple levels and in varying degrees …
and structural (from diffusion MRI) connectivities at multiple levels and in varying degrees …
Multi-task neural networks for joint hippocampus segmentation and clinical score regression
L Cao, L Li, J Zheng, X Fan, F Yin, H Shen… - Multimedia Tools and …, 2018 - Springer
Feature representations extracted from hippocampus in magnetic resonance (MR) images
are widely used in computer-aided Alzheimer's disease (AD) diagnosis, and thus accurate …
are widely used in computer-aided Alzheimer's disease (AD) diagnosis, and thus accurate …
Altered resting state dynamic functional connectivity of amygdala subregions in patients with autism spectrum disorder: a multi-site fMRI study
Y Gao, J Sun, L Cheng, Q Yang, J Li, Z Hao… - Journal of Affective …, 2022 - Elsevier
Background Autism spectrum disorder (ASD) is associated with altered brain connectivity.
Previous studies have focused on the static functional connectivity pattern from amygdala …
Previous studies have focused on the static functional connectivity pattern from amygdala …
A deep network model on dynamic functional connectivity with applications to gender classification and intelligence prediction
L Fan, J Su, J Qin, D Hu, H Shen - Frontiers in neuroscience, 2020 - frontiersin.org
Increasing evidence has suggested that the dynamic properties of functional brain networks
are related to individual behaviors and cognition traits. However, current fMRI-based …
are related to individual behaviors and cognition traits. However, current fMRI-based …
Low-rank graph-regularized structured sparse regression for identifying genetic biomarkers
In this paper, we propose a novel sparse regression method for Brain-Wide and Genome-
Wide association study. Specifically, we impose a low-rank constraint on the weight …
Wide association study. Specifically, we impose a low-rank constraint on the weight …