{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T00:59:38Z","timestamp":1781225978638,"version":"3.54.1"},"reference-count":52,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Knowledge-Based Systems"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.knosys.2026.116036","type":"journal-article","created":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T06:34:29Z","timestamp":1776494069000},"page":"116036","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["A causal adversarial graph neural network for multi-center autism spectrum disorder identification"],"prefix":"10.1016","volume":"343","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-6312-9043","authenticated-orcid":false,"given":"Zhuan","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3753-7691","authenticated-orcid":false,"given":"Qijian","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3656-8330","authenticated-orcid":false,"given":"Li","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1610-1538","authenticated-orcid":false,"given":"Caiqing","family":"Jian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6814-1449","authenticated-orcid":false,"given":"Yue-Min","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5663-1093","authenticated-orcid":false,"given":"Hongjiang","family":"Wei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3558-5112","authenticated-orcid":false,"given":"Lihui","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.knosys.2026.116036_b1","series-title":"Diagnostic and statistical manual of mental disorders: DSM-5","volume":"vol. 5","author":"American Psychiatric Association","year":"2013"},{"issue":"10146","key":"10.1016\/j.knosys.2026.116036_b2","doi-asserted-by":"crossref","first-page":"508","DOI":"10.1016\/S0140-6736(18)31129-2","article-title":"Autism spectrum disorder","volume":"392","author":"Lord","year":"2018","journal-title":"Lancet"},{"key":"10.1016\/j.knosys.2026.116036_b3","doi-asserted-by":"crossref","first-page":"k1674","DOI":"10.1136\/bmj.k1674","article-title":"Autism spectrum disorder: advances in diagnosis and evaluation","volume":"361","author":"Zwaigenbaum","year":"2018","journal-title":"BMJ"},{"issue":"2","key":"10.1016\/j.knosys.2026.116036_b4","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1001\/jama.2022.23661","article-title":"Autism spectrum disorder: A review","volume":"329","author":"Hirota","year":"2023","journal-title":"JAMA"},{"issue":"5","key":"10.1016\/j.knosys.2026.116036_b5","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1001\/jamapsychiatry.2017.4685","article-title":"The emerging clinical neuroscience of autism spectrum disorder: a review","volume":"75","author":"Muhle","year":"2018","journal-title":"JAMA Psychiatry"},{"key":"10.1016\/j.knosys.2026.116036_b6","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.mri.2019.05.031","article-title":"Machine learning in resting-state fMRI analysis","volume":"64","author":"Khosla","year":"2019","journal-title":"Magn. Reson. Imaging"},{"issue":"13","key":"10.1016\/j.knosys.2026.116036_b7","doi-asserted-by":"crossref","first-page":"8122","DOI":"10.1093\/cercor\/bhad103","article-title":"Identifying autism spectrum disorder using edge-centric functional connectivity","volume":"33","author":"Sun","year":"2023","journal-title":"Cerebral Cortex"},{"key":"10.1016\/j.knosys.2026.116036_b8","doi-asserted-by":"crossref","first-page":"70","DOI":"10.3389\/fninf.2019.00070","article-title":"ASD-DiagNet: a hybrid learning approach for detection of autism spectrum disorder using fMRI data","volume":"13","author":"Eslami","year":"2019","journal-title":"Front. Neuroinformatics"},{"key":"10.1016\/j.knosys.2026.116036_b9","series-title":"2021 International Research Conference on Smart Computing and Systems Engineering","first-page":"1","article-title":"Autism spectrum disorder diagnosis support model using inception V3","volume":"vol. 4","author":"Herath","year":"2021"},{"key":"10.1016\/j.knosys.2026.116036_b10","series-title":"2022 2nd International Conference on Advanced Research in Computing","first-page":"171","article-title":"Optimize transfer learning for autism spectrum disorder classification with neuroimaging: A comparative study","author":"Herath","year":"2022"},{"issue":"2","key":"10.1016\/j.knosys.2026.116036_b11","doi-asserted-by":"crossref","DOI":"10.1111\/exsy.13623","article-title":"Autism spectrum disorder identification using multi-model deep ensemble classifier with transfer learning","volume":"42","author":"Herath","year":"2025","journal-title":"Expert Syst."},{"key":"10.1016\/j.knosys.2026.116036_b12","doi-asserted-by":"crossref","first-page":"102475","DOI":"10.1016\/j.artmed.2022.102475","article-title":"DeepMNF: Deep multimodal neuroimaging framework for diagnosing autism spectrum disorder","volume":"136","author":"Abbas","year":"2023","journal-title":"Artificial Intelligence in Medicine"},{"key":"10.1016\/j.knosys.2026.116036_b13","series-title":"2022 International Joint Conference on Neural Networks","first-page":"1","article-title":"Deep dynamic effective connectivity estimation from multivariate time series","author":"Mahmood","year":"2022"},{"key":"10.1016\/j.knosys.2026.116036_b14","series-title":"2023 IEEE 20th International Symposium on Biomedical Imaging","first-page":"1","article-title":"MultiViT: Multimodal vision transformer for schizophrenia prediction using structural MRI and functional network connectivity data","author":"Bi","year":"2023"},{"key":"10.1016\/j.knosys.2026.116036_b15","series-title":"Semi-supervised classification with graph convolutional networks","author":"Kipf","year":"2016"},{"key":"10.1016\/j.knosys.2026.116036_b16","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/j.media.2018.06.001","article-title":"Disease prediction using graph convolutional networks: application to autism spectrum disorder and Alzheimer\u2019s disease","volume":"48","author":"Parisot","year":"2018","journal-title":"Med. Image Anal."},{"issue":"3","key":"10.1016\/j.knosys.2026.116036_b17","doi-asserted-by":"crossref","first-page":"1443","DOI":"10.1109\/JBHI.2022.3229465","article-title":"Multi-graph attention networks with bilinear convolution for diagnosis of schizophrenia","volume":"27","author":"Yu","year":"2023","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"10.1016\/j.knosys.2026.116036_b18","article-title":"Identification of autism spectrum disorder based on functional near-infrared spectroscopy using adaptive spatiotemporal graph convolution network","volume":"17","author":"Zhang","year":"2023","journal-title":"Front. Neurosci."},{"key":"10.1016\/j.knosys.2026.116036_b19","doi-asserted-by":"crossref","first-page":"0467","DOI":"10.34133\/research.0467","article-title":"Causal inference meets deep learning: A comprehensive survey","volume":"7","author":"Jiao","year":"2024","journal-title":"Research"},{"key":"10.1016\/j.knosys.2026.116036_b20","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2023.103043","article-title":"Riemannian frameworks for the harmonization of resting-state functional MRI scans","volume":"91","author":"Honnorat","year":"2024","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.knosys.2026.116036_b21","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2021.102233","article-title":"Braingnn: Interpretable brain graph neural network for fmri analysis","volume":"74","author":"Li","year":"2021","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.knosys.2026.116036_b22","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.neuroimage.2017.01.072","article-title":"Statistical power and prediction accuracy in multisite resting-state fMRI connectivity","volume":"149","author":"Dansereau","year":"2017","journal-title":"Neuroimage"},{"issue":"11","key":"10.1016\/j.knosys.2026.116036_b23","doi-asserted-by":"crossref","first-page":"4213","DOI":"10.1002\/hbm.24241","article-title":"Statistical harmonization corrects site effects in functional connectivity measurements from multi-site fMRI data","volume":"39","author":"Yu","year":"2018","journal-title":"Hum. Brain Mapp."},{"issue":"4","key":"10.1016\/j.knosys.2026.116036_b24","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pbio.3000042","article-title":"Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias","volume":"17","author":"Yamashita","year":"2019","journal-title":"PLoS Biol."},{"key":"10.1016\/j.knosys.2026.116036_b25","series-title":"Proceedings of the 32nd International Conference on Machine Learning - Volume 37","first-page":"1180","article-title":"Unsupervised domain adaptation by backpropagation","author":"Ganin","year":"2015"},{"key":"10.1016\/j.knosys.2026.116036_b26","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2024.103211","article-title":"BrainDAS: Structure-aware domain adaptation network for multi-site brain network analysis","volume":"96","author":"Song","year":"2024","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.knosys.2026.116036_b27","series-title":"International Conference on Learning Representations","article-title":"Discovering invariant rationales for graph neural networks","author":"Wu","year":"2022"},{"key":"10.1016\/j.knosys.2026.116036_b28","series-title":"Proceedings of the 39th International Conference on Machine Learning","first-page":"15524","article-title":"Interpretable and generalizable graph learning via stochastic attention mechanism","volume":"162","author":"Miao","year":"2022"},{"key":"10.1016\/j.knosys.2026.116036_b29","unstructured":"Yongqiang Chen, Yatao Bian, Bo Han, James Cheng, How Interpretable Are Interpretable Graph Neural Networks?, in: Proceedings of the 41st International Conference on Machine Learning, 2024."},{"issue":"5","key":"10.1016\/j.knosys.2026.116036_b30","doi-asserted-by":"crossref","first-page":"947","DOI":"10.1111\/rssb.12167","article-title":"Causal inference by using invariant prediction: identification and confidence intervals","volume":"78","author":"Peters","year":"2016","journal-title":"J. R. Stat. Soc. Ser. B Stat. Methodol."},{"issue":"1","key":"10.1016\/j.knosys.2026.116036_b31","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1109\/TMI.2023.3294182","article-title":"A causality-aware graph convolutional network framework for rigidity assessment in parkinsonians","volume":"43","author":"Tang","year":"2023","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"12","key":"10.1016\/j.knosys.2026.116036_b32","doi-asserted-by":"crossref","first-page":"3752","DOI":"10.1109\/TMI.2023.3305378","article-title":"A causality-driven graph convolutional network for postural abnormality diagnosis in parkinsonians","volume":"42","author":"Tang","year":"2023","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.knosys.2026.116036_b33","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106147","article-title":"Ci-gnn: A granger causality-inspired graph neural network for interpretable brain network-based psychiatric diagnosis","volume":"172","author":"Zheng","year":"2024","journal-title":"Neural Netw."},{"key":"10.1016\/j.knosys.2026.116036_b34","series-title":"Elements of Causal Inference: Foundations and Learning Algorithms","author":"Peters","year":"2017"},{"issue":"27","key":"10.1016\/j.knosys.2026.116036_b35","first-page":"5","article-title":"The neuro bureau preprocessing initiative: open sharing of preprocessed neuroimaging data and derivatives","volume":"7","author":"Craddock","year":"2013","journal-title":"Front. Neuroinformatics"},{"issue":"1","key":"10.1016\/j.knosys.2026.116036_b36","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1038\/s41592-018-0235-4","article-title":"fMRIPrep: a robust preprocessing pipeline for functional MRI","volume":"16","author":"Esteban","year":"2019","journal-title":"Nature Methods"},{"issue":"8","key":"10.1016\/j.knosys.2026.116036_b37","doi-asserted-by":"crossref","first-page":"1914","DOI":"10.1002\/hbm.21333","article-title":"A whole brain fMRI atlas generated via spatially constrained spectral clustering","volume":"33","author":"Craddock","year":"2012","journal-title":"Hum. Brain Mapp."},{"key":"10.1016\/j.knosys.2026.116036_b38","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2022.102375","article-title":"Disease prediction with edge-variational graph convolutional networks","volume":"77","author":"Huang","year":"2022","journal-title":"Med. Image Anal."},{"issue":"6","key":"10.1016\/j.knosys.2026.116036_b39","doi-asserted-by":"crossref","first-page":"7275","DOI":"10.1109\/TNNLS.2022.3154755","article-title":"Adversarial learning based node-edge graph attention networks for autism spectrum disorder identification","volume":"35","author":"Chen","year":"2024","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.knosys.2026.116036_b40","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2024.120594","article-title":"BPI-GNN: Interpretable brain network-based psychiatric diagnosis and subtyping","volume":"292","author":"Zheng","year":"2024","journal-title":"NeuroImage"},{"issue":"7","key":"10.1016\/j.knosys.2026.116036_b41","doi-asserted-by":"crossref","first-page":"13066","DOI":"10.1109\/TNNLS.2024.3449419","article-title":"BrainIB: Interpretable brain network-based psychiatric diagnosis with graph information bottleneck","volume":"36","author":"Zheng","year":"2025","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.knosys.2026.116036_b42","series-title":"International Conference on Learning Representations","article-title":"BrainOOD: Out-of-distribution generalizable brain network analysis","author":"Xu","year":"2025"},{"issue":"12","key":"10.1016\/j.knosys.2026.116036_b43","doi-asserted-by":"crossref","first-page":"18062","DOI":"10.1109\/TNNLS.2023.3311195","article-title":"Site-invariant meta-modulation learning for multisite autism spectrum disorders diagnosis","volume":"35","author":"Lee","year":"2024","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.knosys.2026.116036_b44","series-title":"Decoupled weight decay regularization","author":"Loshchilov","year":"2017"},{"key":"10.1016\/j.knosys.2026.116036_b45","series-title":"How powerful are graph neural networks?","author":"Xu","year":"2018"},{"issue":"7","key":"10.1016\/j.knosys.2026.116036_b46","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0068910","article-title":"BrainNet viewer: a network visualization tool for human brain connectomics","volume":"8","author":"Xia","year":"2013","journal-title":"PloS One"},{"issue":"3","key":"10.1016\/j.knosys.2026.116036_b47","doi-asserted-by":"crossref","first-page":"368","DOI":"10.3390\/brainsci12030368","article-title":"Functional integration and segregation in a multilayer network model of patients with schizophrenia","volume":"12","author":"Wei","year":"2022","journal-title":"Brain Sci."},{"key":"10.1016\/j.knosys.2026.116036_b48","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/j.pnpbp.2017.07.027","article-title":"Resting-state functional under-connectivity within and between large-scale cortical networks across three low-frequency bands in adolescents with autism","volume":"79","author":"Duan","year":"2017","journal-title":"Prog. Neuropsychopharmacol. Biol. Psychiatry"},{"key":"10.1016\/j.knosys.2026.116036_b49","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.neuroimage.2018.01.022","article-title":"Idiosyncratic organization of cortical networks in autism spectrum disorder","volume":"190","author":"Nunes","year":"2019","journal-title":"Neuroimage"},{"issue":"1","key":"10.1016\/j.knosys.2026.116036_b50","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.neuroimage.2010.05.067","article-title":"Abnormal functional connectivity of default mode sub-networks in autism spectrum disorder patients","volume":"53","author":"Assaf","year":"2010","journal-title":"Neuroimage"},{"issue":"1","key":"10.1016\/j.knosys.2026.116036_b51","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1002\/aur.1496","article-title":"Altered medial frontal and superior temporal response to implicit processing of emotions in autism","volume":"9","author":"Kana","year":"2016","journal-title":"Autism Res."},{"key":"10.1016\/j.knosys.2026.116036_b52","doi-asserted-by":"crossref","first-page":"475","DOI":"10.3389\/fphys.2018.00475","article-title":"Abnormal functional connectivity of resting state network detection based on linear ICA analysis in autism spectrum disorder","volume":"9","author":"Bi","year":"2018","journal-title":"Front. Physiol."}],"container-title":["Knowledge-Based Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705126007628?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705126007628?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T00:17:59Z","timestamp":1781223479000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0950705126007628"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":52,"alternative-id":["S0950705126007628"],"URL":"https:\/\/doi.org\/10.1016\/j.knosys.2026.116036","relation":{},"ISSN":["0950-7051"],"issn-type":[{"value":"0950-7051","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A causal adversarial graph neural network for multi-center autism spectrum disorder identification","name":"articletitle","label":"Article Title"},{"value":"Knowledge-Based Systems","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.knosys.2026.116036","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"116036"}}