Brain imaging-based machine learning in autism spectrum disorder: methods and applications

M Xu, V Calhoun, R Jiang, W Yan, J Sui - Journal of neuroscience methods, 2021‏ - Elsevier
Autism spectrum disorder (ASD) is a neurodevelopmental condition with early childhood
onset and high heterogeneity. As the pathogenesis is still elusive, ASD diagnosis is …

The promise of precision functional map** for neuroimaging in psychiatry

DV Demeter, DJ Greene - Neuropsychopharmacology, 2024‏ - nature.com
Precision functional map** (PFM) is a neuroimaging approach to reliably estimate metrics
of brain function from individual people via the collection of large amounts of fMRI data …

Autism spectrum disorder detection framework for children based on federated learning integrated CNN-LSTM

A Lakhan, MA Mohammed, KH Abdulkareem… - Computers in Biology …, 2023‏ - Elsevier
Abstract The incidence of Autism Spectrum Disorder (ASD) among children, attributed to
genetics and environmental factors, has been increasing daily. ASD is a non-curable …

Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network

S Qi, J Sui, G Pearlson, J Bustillo… - Nature …, 2022‏ - nature.com
Schizophrenia is a highly heritable psychiatric disorder characterized by widespread
functional and structural brain abnormalities. However, previous association studies …

Inter-individual heterogeneity of functional brain networks in children with autism spectrum disorder

X Guo, G Zhai, J Liu, Y Cao, X Zhang, D Cui, L Gao - Molecular Autism, 2022‏ - Springer
Background Autism spectrum disorder (ASD) is a neurodevelopmental disorder with
considerable clinical heterogeneity. This study aimed to explore the heterogeneity of ASD …

Interpreting brain biomarkers: Challenges and solutions in interpreting machine learning-based predictive neuroimaging

R Jiang, CW Woo, S Qi, J Wu… - IEEE signal processing …, 2022‏ - ieeexplore.ieee.org
Predictive modeling of neuroimaging data (predictive neuroimaging) for evaluating
individual differences in various behavioral phenotypes and clinical outcomes is of growing …

Disrupted network integration and segregation involving the default mode network in autism spectrum disorder

B Yang, M Wang, W Zhou, X Wang, S Chen… - Journal of Affective …, 2023‏ - Elsevier
Abstract Changes in the brain's default mode network (DMN) in the resting state are closely
related to autism spectrum disorder (ASD). Module segmentation can effectively elucidate …

Data-driven multimodal fusion: approaches and applications in psychiatric research

J Sui, D Zhi, VD Calhoun - Psychoradiology, 2023‏ - academic.oup.com
In the era of big data, where vast amounts of information are being generated and collected
at an unprecedented rate, there is a pressing demand for innovative data-driven multi-modal …

[HTML][HTML] Stratifying ASD and characterizing the functional connectivity of subtypes in resting-state fMRI

P Ren, Q Bi, W Pang, M Wang, Q Zhou, X Ye… - Behavioural Brain …, 2023‏ - Elsevier
Abstracts Background Although stratifying autism spectrum disorder (ASD) into different
subtypes is a common effort in the research field, few papers have characterized the …

Reduced covariation between brain morphometry and local spontaneous activity in young children with ASD

B Chen, L Olson, A Rios, M Salmina, A Linke… - Cerebral …, 2024‏ - academic.oup.com
While disruptions in brain maturation in the first years of life in ASD are well documented,
little is known about how the brain structure and function are related in young children with …