{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,28]],"date-time":"2025-09-28T04:18:00Z","timestamp":1759033080441,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030322809"},{"type":"electronic","value":"9783030322816"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-3-030-32281-6_11","type":"book-chapter","created":{"date-parts":[[2019,10,10]],"date-time":"2019-10-10T15:02:46Z","timestamp":1570719766000},"page":"105-114","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Hierarchical Adversarial Connectomic Domain Alignment for Target Brain Graph Prediction and Classification from a Source Graph"],"prefix":"10.1007","author":[{"given":"Alaa","family":"Bessadok","sequence":"first","affiliation":[]},{"given":"Mohamed Ali","family":"Mahjoub","sequence":"additional","affiliation":[]},{"given":"Islem","family":"Rekik","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,10,10]]},"reference":[{"key":"11_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1007\/978-3-319-10443-0_39","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2014","author":"R Li","year":"2014","unstructured":"Li, R., et al.: Deep learning based imaging data completion for improved brain disease diagnosis. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds.) MICCAI 2014. LNCS, vol. 8675, pp. 305\u2013312. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10443-0_39"},{"key":"11_CR2","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1016\/j.engappai.2018.11.013","volume":"78","author":"A Ben-Cohen","year":"2019","unstructured":"Ben-Cohen, A., et al.: Cross-modality synthesis from CT to PET using FCN and GAN networks for improved automated lesion detection. Eng. Appl. Artif. Intell. 78, 186\u2013194 (2019)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"11_CR3","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. Advances in Neural Information Processing Systems, pp. 2672\u20132680 (2014)"},{"key":"11_CR4","doi-asserted-by":"crossref","unstructured":"Arslan, S., Ktena, S.I., Glocker, B., Rueckert, D.: Graph saliency maps through spectral convolutional networks: Application to sex classification with brain connectivity. arXiv preprint arXiv:1806.01764 (2018)","DOI":"10.1007\/978-3-030-00689-1_1"},{"key":"11_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1007\/978-3-319-66182-7_54","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2017","author":"SI Ktena","year":"2017","unstructured":"Ktena, S.I., et al.: Distance metric learning using graph convolutional networks: application to functional brain networks. In: Descoteaux, M., Maier-Hein, L., Franz, A., Jannin, P., Collins, D.L., Duchesne, S. (eds.) MICCAI 2017. LNCS, vol. 10433, pp. 469\u2013477. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-66182-7_54"},{"key":"11_CR6","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)"},{"key":"11_CR7","doi-asserted-by":"crossref","unstructured":"Olut, S., Sahin, Y.H., Demir, U., Unal, G.: Generative adversarial training for MRA image synthesis using multi-contrast MRI. arXiv preprint arXiv:1804.04366 (2018)","DOI":"10.1007\/978-3-030-00320-3_18"},{"key":"11_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1007\/978-3-030-00889-5_20","volume-title":"Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support","author":"H Yang","year":"2018","unstructured":"Yang, H., et al.: Unpaired brain MR-to-CT synthesis using a structure-constrained CycleGAN. In: Stoyanov, D., et al. (eds.) DLMIA\/ML-CDS -2018. LNCS, vol. 11045, pp. 174\u2013182. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-00889-5_20"},{"key":"11_CR9","unstructured":"Soussia, M., Rekik, I.: A review on image-and network-based brain data analysis techniques for Alzheimer\u2019s disease diagnosis reveals a gap in developing predictive methods for prognosis. arXiv preprint arXiv:1808.01951 (2018)"},{"key":"11_CR10","doi-asserted-by":"crossref","unstructured":"Pan, S., Hu, R., Long, G., Jiang, J., Yao, L., Zhang, C.: Adversarially regularized graph autoencoder. arXiv preprint arXiv:1802.04407 (2018)","DOI":"10.24963\/ijcai.2018\/362"},{"key":"11_CR11","doi-asserted-by":"publisher","first-page":"4103","DOI":"10.1038\/s41598-018-21568-7","volume":"8","author":"I Mahjoub","year":"2018","unstructured":"Mahjoub, I., Mahjoub, M.A., Rekik, I.: Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states. Sci. Rep. 8, 4103 (2018)","journal-title":"Sci. Rep."},{"key":"11_CR12","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1089\/brain.2018.0578","volume":"9","author":"A Lisowska","year":"2018","unstructured":"Lisowska, A., Rekik, I.: Alzheimer\u2019s disease neuroimaging initiative and others: joint pairing and structured mapping of convolutional brain morphological multiplexes for early dementia diagnosis. Brain Connect. 9, 22\u201336 (2018)","journal-title":"Brain Connect."},{"key":"11_CR13","doi-asserted-by":"publisher","first-page":"43830","DOI":"10.1109\/ACCESS.2018.2863657","volume":"6","author":"R Raeper","year":"2018","unstructured":"Raeper, R., Lisowska, A., Rekik, I.: Cooperative correlational and discriminative ensemble classifier learning for early dementia diagnosis using morphological brain multiplexes. IEEE Access 6, 43830\u201343839 (2018)","journal-title":"IEEE Access"},{"key":"11_CR14","doi-asserted-by":"crossref","unstructured":"Soussia, M., Rekik, I.:Unsupervised manifold learning using high-order morphological brain networks derived from T1-w MRI for autism diagnosis. Front. Neuroinf. 12 (2018)","DOI":"10.3389\/fninf.2018.00070"},{"key":"11_CR15","doi-asserted-by":"crossref","unstructured":"Wang, B., Ramazzotti, D., De Sano, L., Zhu, J., Pierson, E., Batzoglou, S.: SIMLR: a tool for large-scale single-cell analysis by multi-kernel learning. bioRxiv p. 118901 (2017)","DOI":"10.1101\/118901"},{"key":"11_CR16","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45, 5\u201332 (2001)","journal-title":"Mach. Learn."},{"key":"11_CR17","doi-asserted-by":"publisher","first-page":"774","DOI":"10.1016\/j.neuroimage.2012.01.021","volume":"62","author":"B Fischl","year":"2012","unstructured":"Fischl, B.: Freesurfer. Neuroimage 62, 774\u2013781 (2012)","journal-title":"Neuroimage"}],"container-title":["Lecture Notes in Computer Science","Predictive Intelligence in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-32281-6_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,10]],"date-time":"2024-10-10T00:07:43Z","timestamp":1728518863000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-32281-6_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030322809","9783030322816"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-32281-6_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"10 October 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRIME","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on PRedictive Intelligence In MEdicine","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shenzhen","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":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 October 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 October 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"prime2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/basira-lab.com\/prime-miccai19\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}