{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T10:11:45Z","timestamp":1743156705250,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":22,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819756889"},{"type":"electronic","value":"9789819756896"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-97-5689-6_24","type":"book-chapter","created":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T08:02:35Z","timestamp":1722326555000},"page":"276-286","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-atlas Hypergraph Fusion Based on Brain Regions Overlap Amount for Diagnosis of ASD"],"prefix":"10.1007","author":[{"given":"Huajian","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaochen","family":"Mu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tengfei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianan","family":"Ning","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuefeng","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,7,31]]},"reference":[{"key":"24_CR1","doi-asserted-by":"crossref","unstructured":"American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders: DSM-5, vol. 5. American Psychiatric Association Washington, DC (2013)","DOI":"10.1176\/appi.books.9780890425596"},{"key":"24_CR2","doi-asserted-by":"crossref","unstructured":"An, L., Chen, X., Yang, S., Li, X.: Person re-identification by multi-hypergraph fusion. IEEE Trans. Neural Netw. Learn. Syst. 28(11), 2763\u20132774 (2016)","DOI":"10.1109\/TNNLS.2016.2602082"},{"key":"24_CR3","doi-asserted-by":"crossref","unstructured":"Chen, H., et al.: Multivariate classification of autism spectrum disorder using frequency-specific resting-state functional connectivity\u2014a multi-center study. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 64, 1\u20139 (2016)","DOI":"10.1016\/j.pnpbp.2015.06.014"},{"key":"24_CR4","unstructured":"Chen, Y., et al.: Adversarial learning based node-edge graph attention networks for autism spectrum disorder identification. IEEE Trans. Neural Netw. Learn. Syst. (2022)"},{"key":"24_CR5","doi-asserted-by":"crossref","unstructured":"Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20, 273\u2013297 (1995)","DOI":"10.1007\/BF00994018"},{"key":"24_CR6","doi-asserted-by":"crossref","unstructured":"Craddock, R.C., James, G.A., Holtzheimer III, P.E., Hu, X.P., Mayberg, H.S.: A whole brain fMRI atlas generated via spatially constrained spectral clustering. Human Brain Mapp. 33(8), 1914\u20131928 (2012)","DOI":"10.1002\/hbm.21333"},{"key":"24_CR7","doi-asserted-by":"crossref","unstructured":"Di Martino, A., et al.: The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Mol. Psychiatry 19(6), 659\u2013667 (2014)","DOI":"10.1038\/mp.2013.78"},{"key":"24_CR8","doi-asserted-by":"crossref","unstructured":"Eslami, T., Mirjalili, V., Fong, A., Laird, A.R., Saeed, F.: ASD-DiagNet: a hybrid learning approach for detection of autism spectrum disorder using fMRI data. Front. Neuroinform. 13, 70 (2019)","DOI":"10.3389\/fninf.2019.00070"},{"key":"24_CR9","doi-asserted-by":"crossref","unstructured":"Farooq, M.S., Tehseen, R., Sabir, M., Atal, Z.: Detection of autism spectrum disorder (ASD) in children and adults using machine learning. Sci. Rep. 13(1), 9605 (2023)","DOI":"10.1038\/s41598-023-35910-1"},{"key":"24_CR10","doi-asserted-by":"crossref","unstructured":"Huang, Z.A., Zhu, Z., Yau, C.H., Tan, K.C.: Identifying autism spectrum disorder from resting-state fMRI using deep belief network. IEEE Trans. Neural Netw. Learn. Syst. 32(7), 2847\u20132861 (2020)","DOI":"10.1109\/TNNLS.2020.3007943"},{"key":"24_CR11","doi-asserted-by":"crossref","unstructured":"Kong, Y., Gao, J., Xu, Y., Pan, Y., Wang, J., Liu, J.: Classification of autism spectrum disorder by combining brain connectivity and deep neural network classifier. Neurocomputing 324, 63\u201368 (2019)","DOI":"10.1016\/j.neucom.2018.04.080"},{"key":"24_CR12","doi-asserted-by":"crossref","unstructured":"Li, X., et al.: BrainGNN: interpretable brain graph neural network for fMRI analysis, vol. 74, p. 102233. Elsevier (2021)","DOI":"10.1016\/j.media.2021.102233"},{"key":"24_CR13","doi-asserted-by":"crossref","unstructured":"Liu, J., et al.: Applications of deep learning to MRI images: a survey. Big Data Mining Analytics 1(1), 1\u201318 (2018)","DOI":"10.26599\/BDMA.2018.9020001"},{"key":"24_CR14","doi-asserted-by":"crossref","unstructured":"Parisot, S., et al.: Disease prediction using graph convolutional networks: application to autism spectrum disorder and Alzheimer\u2019s disease. Med. Image Anal. 48, 117\u2013130 (2018)","DOI":"10.1016\/j.media.2018.06.001"},{"key":"24_CR15","doi-asserted-by":"crossref","unstructured":"Power, J.D., et al.: Functional network organization of the human brain. Neuron 72(4), 665\u2013678 (2011)","DOI":"10.1016\/j.neuron.2011.09.006"},{"key":"24_CR16","doi-asserted-by":"crossref","unstructured":"Wang, K.: Robust embedding framework with dynamic hypergraph fusion for multi-label classification. In: 2019 IEEE International Conference on Multimedia and Expo (ICME), pp. 982\u2013987. IEEE (2019)","DOI":"10.1109\/ICME.2019.00173"},{"key":"24_CR17","doi-asserted-by":"crossref","unstructured":"Wang, Y., Liu, J., Xiang, Y., Wang, J., Chen, Q., Chong, J.: MAGE: automatic diagnosis of autism spectrum disorders using multi-atlas graph convolutional networks and ensemble learning. Neurocomputing 469, 346\u2013353 (2022)","DOI":"10.1016\/j.neucom.2020.06.152"},{"key":"24_CR18","doi-asserted-by":"crossref","unstructured":"Wang, Y., Wang, J., Wu, F.X., Hayrat, R., Liu, J.: AIMAFE: autism spectrum disorder identification with multi-atlas deep feature representation and ensemble learning. J. Neurosci. Methods 343, 108840 (2020)","DOI":"10.1016\/j.jneumeth.2020.108840"},{"key":"24_CR19","doi-asserted-by":"crossref","unstructured":"Wen, G., Cao, P., Bao, H., Yang, W., Zheng, T., Zaiane, O.: MVS-GCN: a prior brain structure learning-guided multi-view graph convolution network for autism spectrum disorder diagnosis. Compu. Biol. Med. 142, 105239 (2022)","DOI":"10.1016\/j.compbiomed.2022.105239"},{"key":"24_CR20","doi-asserted-by":"crossref","unstructured":"Yin, W., Li, L., Wu, F.X.: A graph attention neural network for diagnosing ASD with fMRI data. In: 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 1131\u20131136. IEEE (2021)","DOI":"10.1109\/BIBM52615.2021.9669849"},{"key":"24_CR21","doi-asserted-by":"crossref","unstructured":"Zhou, D., Huang, J., Sch\u00f6lkopf, B.: Learning with hypergraphs: clustering, classification, and embedding. In: Advances in Neural Information Processing Systems, vol. 19 (2006)","DOI":"10.7551\/mitpress\/7503.003.0205"},{"key":"24_CR22","doi-asserted-by":"publisher","unstructured":"Zuo, Q., Lei, B., Shen, Y., Liu, Y., Feng, Z., Wang, S.: Multimodal representations learning and adversarial hypergraph fusion for early Alzheimer\u2019s disease prediction. In: Ma, H., et al. (eds.) Pattern Recognition and Computer Vision: 4th Chinese Conference, PRCV 2021, Beijing, China, 29 October\u20131 November 2021, Proceedings, Part III 4. pp. 479\u2013490. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-88010-1_40","DOI":"10.1007\/978-3-030-88010-1_40"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-5689-6_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T08:06:08Z","timestamp":1722326768000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-5689-6_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819756889","9789819756896"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-5689-6_24","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"31 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tianjin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 August 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 August 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2024\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}