{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T10:08:54Z","timestamp":1759226934708},"publisher-location":"Cham","reference-count":14,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319973036"},{"type":"electronic","value":"9783319973043"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-97304-3_82","type":"book-chapter","created":{"date-parts":[[2018,7,26]],"date-time":"2018-07-26T14:34:06Z","timestamp":1532615646000},"page":"1069-1080","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Node Based Row-Filter Convolutional Neural Network for Brain Network Classification"],"prefix":"10.1007","author":[{"given":"Bingcheng","family":"Mao","sequence":"first","affiliation":[]},{"given":"Jiashuang","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Daoqiang","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,7,27]]},"reference":[{"issue":"3","key":"82_CR1","doi-asserted-by":"publisher","first-page":"1059","DOI":"10.1016\/j.neuroimage.2009.10.003","volume":"52","author":"M Rubinov","year":"2010","unstructured":"Rubinov, M., Sporns, O.: Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52(3), 1059\u20131069 (2010)","journal-title":"Neuroimage"},{"issue":"7","key":"82_CR2","doi-asserted-by":"publisher","first-page":"2876","DOI":"10.1002\/hbm.22353","volume":"35","author":"B Jie","year":"2014","unstructured":"Jie, B., Zhang, D., Wee, C.Y., Shen, D.: Topological graph kernel on multiple thresholded functional connectivity networks for mild cognitive impairment classification. Hum. Brain Mapp. 35(7), 2876 (2014)","journal-title":"Hum. Brain Mapp."},{"issue":"5","key":"82_CR3","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1089\/brain.2013.0214","volume":"4","author":"F Fei","year":"2014","unstructured":"Fei, F., Jie, B., Zhang, D.: Frequent and discriminative subnetwork mining for mild cognitive impairment classification. Brain Connect. 4(5), 347\u2013360 (2014)","journal-title":"Brain Connect."},{"issue":"2","key":"82_CR4","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1002\/hbm.20517","volume":"30","author":"M Rubinov","year":"2009","unstructured":"Rubinov, M., et al.: Small-world properties of nonlinear brain activity in schizophrenia. Hum. Brain Mapp. 30(2), 403\u2013416 (2009)","journal-title":"Hum. Brain Mapp."},{"key":"82_CR5","doi-asserted-by":"publisher","first-page":"21","DOI":"10.3389\/fpsyt.2015.00021","volume":"6","author":"MD Sacchet","year":"2015","unstructured":"Sacchet, M.D., Prasad, G., Foland-Ross, L.C., Thompson, P.M., Gotlib, I.H.: Support vector machine classification of major depressive disorder using diffusion-weighted neuroimaging and graph theory. Front. Psychiatry 6, 21 (2015)","journal-title":"Front. Psychiatry"},{"key":"82_CR6","unstructured":"Verma, S., Zhang, Z.L.: Hunt for the unique, stable, sparse and fast feature learning on graphs. In: Advances in Neural Information Processing Systems, pp. 87\u201397 (2017)"},{"issue":"7553","key":"82_CR7","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436\u2013444 (2015)","journal-title":"Nature"},{"key":"82_CR8","unstructured":"Atwood, J., Towsley, D.: Diffusion-convolutional neural networks. In: Advances in Neural Information Processing Systems, pp. 1993\u20132001 (2016)"},{"key":"82_CR9","unstructured":"Bruna, J., Zaremba, W., Szlam, A., LeCun, Y.: Spectral networks and locally connected networks on graphs. arXiv preprint \narXiv:1312.6203\n\n (2013)"},{"key":"82_CR10","unstructured":"Duvenaud, D.K., et al.: Convolutional networks on graphs for learning molecular fingerprints. In: Advances in Neural Information Processing Systems, pp. 2224\u20132232 (2015)"},{"key":"82_CR11","doi-asserted-by":"crossref","unstructured":"Wang, S., He, L., Cao, B., Lu, C.T., Yu, P.S., Ragin, A.B.: Structural deep brain network mining. In: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 475\u2013484. ACM (2017)","DOI":"10.1145\/3097983.3097988"},{"issue":"10","key":"82_CR12","doi-asserted-by":"publisher","first-page":"2125","DOI":"10.1109\/TKDE.2017.2720734","volume":"29","author":"Z Luo","year":"2017","unstructured":"Luo, Z., Liu, L., Yin, J., Li, Y., Wu, Z.: Deep learning of graphs with Ngram convolutional neural networks. IEEE Trans. Knowl. Data Eng. 29(10), 2125\u20132139 (2017)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"82_CR13","unstructured":"Defferrard, M., Bresson, X., Vandergheynst, P.: Convolutional neural networks on graphs with fast localized spectral filtering. In: Advances in Neural Information Processing Systems, pp. 3844\u20133852 (2016)"},{"key":"82_CR14","unstructured":"INDI Homepage. http:\/\/fcon_1000.projects.nitrc.org\/. Accessed 12 Nov 2017"}],"container-title":["Lecture Notes in Computer Science","PRICAI 2018: Trends in Artificial Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-97304-3_82","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,7,26]],"date-time":"2018-07-26T15:27:41Z","timestamp":1532618861000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-97304-3_82"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319973036","9783319973043"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-97304-3_82","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]}}}