{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T15:19:36Z","timestamp":1778080776104,"version":"3.51.4"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031720857","type":"print"},{"value":"9783031720864","type":"electronic"}],"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\/978-3-031-72086-4_48","type":"book-chapter","created":{"date-parts":[[2024,10,3]],"date-time":"2024-10-03T20:34:45Z","timestamp":1727987685000},"page":"511-521","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Multi-modal Graph Neural Network with Transformer-Guided Adaptive Diffusion for Preclinical Alzheimer Classification"],"prefix":"10.1007","author":[{"given":"Jaeyoon","family":"Sim","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minjae","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guorong","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Won Hwa","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,10,4]]},"reference":[{"key":"48_CR1","unstructured":"Ba, J.L., Kiros, J.R., Hinton, G.E.: Layer normalization. Advances in Neural Information Processing Systems (2016)"},{"key":"48_CR2","unstructured":"Chung, F.R.: Spectral graph theory, vol.\u00a092. American Mathematical Soc. (1997)"},{"issue":"1","key":"48_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.neuroimage.2010.06.010","volume":"53","author":"C Destrieux","year":"2010","unstructured":"Destrieux, C., Fischl, B., Dale, A., Halgren, E.: Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature. Neuroimage 53(1), 1\u201315 (2010)","journal-title":"Neuroimage"},{"issue":"1","key":"48_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13024-019-0333-5","volume":"14","author":"MA DeTure","year":"2019","unstructured":"DeTure, M.A., Dickson, D.W.: The neuropathological diagnosis of Alzheimer\u2019s disease. Molecular neurodegeneration 14(1), 1\u201318 (2019)","journal-title":"Molecular neurodegeneration"},{"key":"48_CR5","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Annual Meeting of the Association for Computational Linguistics (2019)"},{"key":"48_CR6","unstructured":"Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., et\u00a0al.: An image is worth 16x16 words: Transformers for image recognition at scale. International Conference on Learning Representations (2021)"},{"key":"48_CR7","unstructured":"Gasteiger, J., Wei\u00dfenberger, S., G\u00fcnnemann, S.: Diffusion improves graph learning. Advances in Neural Information Processing Systems 32 (2019)"},{"key":"48_CR8","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Computer Vision and Pattern Recognition. pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"issue":"12","key":"48_CR9","doi-asserted-by":"publisher","first-page":"3277","DOI":"10.1093\/brain\/awn278","volume":"131","author":"LW de Jong","year":"2008","unstructured":"de\u00a0Jong, L.W., van\u00a0der Hiele, K., Veer, I.M., Houwing, J., Westendorp, R., Bollen, E., de\u00a0Bruin, P.W., Middelkoop, H., van Buchem, M.A., van\u00a0der Grond, J.: Strongly reduced volumes of putamen and thalamus in Alzheimer\u2019s disease: an MRI study. Brain 131(12), 3277\u20133285 (2008)","journal-title":"Brain"},{"issue":"11","key":"48_CR10","doi-asserted-by":"publisher","first-page":"2132","DOI":"10.1016\/j.clinph.2015.02.060","volume":"126","author":"A Khazaee","year":"2015","unstructured":"Khazaee, A., Ebrahimzadeh, A., Babajani-Feremi, A.: Identifying patients with Alzheimer\u2019s disease using resting-state fMRI and graph theory. Clinical Neurophysiology 126(11), 2132\u20132141 (2015)","journal-title":"Clinical Neurophysiology"},{"key":"48_CR11","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.neuroimage.2015.05.050","volume":"118","author":"WH Kim","year":"2015","unstructured":"Kim, W.H., Adluru, N., Chung, M.K., Okonkwo, O.C., Johnson, S.C., Bendlin, B.B., Singh, V.: Multi-resolution statistical analysis of brain connectivity graphs in preclinical Alzheimer\u2019s disease. NeuroImage 118, 103\u2013117 (2015)","journal-title":"NeuroImage"},{"key":"48_CR12","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. International Conference on Learning Representations (2017)"},{"key":"48_CR13","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1016\/j.bbr.2017.01.037","volume":"326","author":"X Liu","year":"2017","unstructured":"Liu, X., Chen, W., Hou, H., Chen, X., Zhang, J., Liu, J., Guo, Z., Bai, G.: Decreased functional connectivity between the dorsal anterior cingulate cortex and lingual gyrus in Alzheimer\u2019s disease patients with depression. Behavioural brain research 326, 132\u2013138 (2017)","journal-title":"Behavioural brain research"},{"key":"48_CR14","volume-title":"Signals and systems","author":"AV Oppenheim","year":"1997","unstructured":"Oppenheim, A.V., Willsky, A.S., Nawab, S.H., Ding, J.J.: Signals and systems, vol.\u00a02. Prentice hall Upper Saddle River, NJ (1997)"},{"key":"48_CR15","doi-asserted-by":"crossref","unstructured":"Park, J., Hwang, Y., Kim, M., Chung, M.K., Wu, G., Kim, W.H.: Convolving directed graph edges via Hodge Laplacian for brain network analysis. In: International Conference on Medical Image Computing and Computer-Assisted Intervention. pp. 789\u2013799. Springer (2023)","DOI":"10.1007\/978-3-031-43904-9_76"},{"key":"48_CR16","doi-asserted-by":"crossref","unstructured":"Rao, Y.L., Ganaraja, B., Murlimanju, B., Joy, T., Krishnamurthy, A., Agrawal, A.: Hippocampus and its involvement in Alzheimer\u2019s disease: a review. 3 Biotech 12(2), \u00a055 (2022)","DOI":"10.1007\/s13205-022-03123-4"},{"issue":"4","key":"48_CR17","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1162\/netn_a_00047","volume":"2","author":"E Ryypp\u00f6","year":"2018","unstructured":"Ryypp\u00f6, E., Glerean, E., Brattico, E., Saram\u00e4ki, J., Korhonen, O.: Regions of interest as nodes of dynamic functional brain networks. Network Neuroscience 2(4), 513\u2013535 (2018)","journal-title":"Network Neuroscience"},{"key":"48_CR18","doi-asserted-by":"crossref","unstructured":"Sim, J., Jeon, S., Choi, I., Wu, G., Kim, W.H.: Learning to approximate adaptive kernel convolution on graphs. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol.\u00a038, pp. 4882\u20134890 (2024)","DOI":"10.1609\/aaai.v38i5.28291"},{"key":"48_CR19","doi-asserted-by":"crossref","unstructured":"Stam, C.J., De\u00a0Haan, W., Daffertshofer, A., Jones, B., Manshanden, I., van Cappellen\u00a0van Walsum, A.M., Montez, T., Verbunt, J., De\u00a0Munck, J.C., Van\u00a0Dijk, B.W., et\u00a0al.: Graph theoretical analysis of magnetoencephalographic functional connectivity in Alzheimer\u2019s disease. Brain 132(1), 213\u2013224 (2009)","DOI":"10.1093\/brain\/awn262"},{"issue":"9","key":"48_CR20","first-page":"1431","volume":"45","author":"JA Thie","year":"2004","unstructured":"Thie, J.A.: Understanding the standardized uptake value, its methods, and implications for usage. Journal of Nuclear Medicine 45(9), 1431\u20131434 (2004)","journal-title":"Journal of Nuclear Medicine"},{"key":"48_CR21","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., Polosukhin, I.: Attention is all you need. Advances in Neural Information Processing Systems 30 (2017)"},{"key":"48_CR22","unstructured":"Veli\u010dkovi\u0107, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., Bengio, Y.: Graph attention networks. International Conference on Learning Representations (2018)"},{"key":"48_CR23","unstructured":"Wu, Q., Yang, C., Zhao, W., He, Y., Wipf, D., Yan, J.: Difformer: Scalable (graph) transformers induced by energy constrained diffusion. International Conference on Learning Representations (2023)"},{"key":"48_CR24","first-page":"27387","volume":"35","author":"Q Wu","year":"2022","unstructured":"Wu, Q., Zhao, W., Li, Z., Wipf, D.P., Yan, J.: Nodeformer: A scalable graph structure learning transformer for node classification. Advances in Neural Information Processing Systems 35, 27387\u201327401 (2022)","journal-title":"Advances in Neural Information Processing Systems"},{"key":"48_CR25","unstructured":"Wu, Q., Zhao, W., Yang, C., Zhang, H., Nie, F., Jiang, H., Bian, Y., Yan, J.: Simplifying and empowering transformers for large-graph representations. Advances in Neural Information Processing Systems 36 (2024)"},{"key":"48_CR26","doi-asserted-by":"crossref","unstructured":"Xu, B., Shen, H., Cao, Q., Cen, K., Cheng, X.: Graph convolutional networks using heat kernel for semi-supervised learning. International Joint Conference on Artificial Intelligence (2019)","DOI":"10.24963\/ijcai.2019\/267"},{"key":"48_CR27","first-page":"23321","volume":"34","author":"J Zhao","year":"2021","unstructured":"Zhao, J., Dong, Y., Ding, M., Kharlamov, E., Tang, J.: Adaptive diffusion in graph neural networks. Advances in Neural Information Processing Systems 34, 23321\u201323333 (2021)","journal-title":"Advances in Neural Information Processing Systems"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72086-4_48","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,3]],"date-time":"2024-10-03T20:40:32Z","timestamp":1727988032000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72086-4_48"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031720857","9783031720864"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72086-4_48","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"4 October 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\u00a0are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"MICCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Medical Image Computing and Computer-Assisted Intervention","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Marrakesh","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Morocco","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":"7 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conferences.miccai.org\/2024\/en\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}