{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T16:06:15Z","timestamp":1759334775055,"version":"build-2065373602"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030593537"},{"type":"electronic","value":"9783030593544"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-59354-4_3","type":"book-chapter","created":{"date-parts":[[2020,9,30]],"date-time":"2020-09-30T19:05:43Z","timestamp":1601492743000},"page":"24-34","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Adversarial Brain Multiplex Prediction from a Single Network for High-Order Connectional Gender-Specific Brain Mapping"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4565-4502","authenticated-orcid":false,"given":"Ahmed","family":"Nebli","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5595-6673","authenticated-orcid":false,"given":"Islem","family":"Rekik","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,10,1]]},"reference":[{"key":"3_CR1","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1177\/1073858410386492","volume":"17","author":"G Gong","year":"2011","unstructured":"Gong, G., He, Y., Evans, A.C.: Brain connectivity: gender makes a difference. Neuroscientist 17, 575\u2013591 (2011)","journal-title":"Neuroscientist"},{"key":"3_CR2","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1007\/s00406-005-0566-x","volume":"255","author":"N Shirao","year":"2005","unstructured":"Shirao, N., Okamoto, Y., Okada, G., Ueda, K., Yamawaki, S.: Gender differences in brain activity toward unpleasant linguistic stimuli concerning interpersonal relationships: an fMRI study. Eur. Arch. Psychiatry Clin. Neurosci. 255, 327\u2013333 (2005). https:\/\/doi.org\/10.1007\/s00406-005-0566-x","journal-title":"Eur. Arch. Psychiatry Clin. Neurosci."},{"key":"3_CR3","doi-asserted-by":"publisher","first-page":"838","DOI":"10.1093\/ije\/22.5.838","volume":"22","author":"PA Saunders","year":"1993","unstructured":"Saunders, P.A., et al.: The prevalence of dementia, depression and neurosis in later life: the Liverpool MRC-ALPHA study. Int. J. Epidemiol. 22, 838\u2013847 (1993)","journal-title":"Int. J. Epidemiol."},{"key":"3_CR4","doi-asserted-by":"publisher","unstructured":"Nebli, Ahmed, Rekik, Islem: Gender differences in cortical morphological networks. Brain Imaging Behav. 1\u20139 (2019). https:\/\/doi.org\/10.1007\/s11682-019-00123-6","DOI":"10.1007\/s11682-019-00123-6"},{"key":"3_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1007\/978-3-030-00928-1_68","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2018","author":"R Raeper","year":"2018","unstructured":"Raeper, R., Lisowska, A., Rekik, I., The Alzheimer\u2019s Disease Neuroimaging Initiative: Joint correlational and discriminative ensemble classifier learning for dementia stratification using shallow brain multiplexes. In: Frangi, A.F., Schnabel, J.A., Davatzikos, C., Alberola-L\u00f3pez, C., Fichtinger, G. (eds.) MICCAI 2018. LNCS, vol. 11070, pp. 599\u2013607. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-00928-1_68"},{"key":"3_CR6","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":"3_CR7","doi-asserted-by":"crossref","unstructured":"Yi, X., Walia, E., Babyn, P.: Generative adversarial network in medical imaging: a review. arXiv preprint arXiv:1809.07294 (2018)","DOI":"10.1016\/j.media.2019.101552"},{"key":"3_CR8","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/MSP.2017.2693418","volume":"34","author":"MM Bronstein","year":"2017","unstructured":"Bronstein, M.M., Bruna, J., LeCun, Y., Szlam, A., Vandergheynst, P.: Geometric deep learning: going beyond Euclidean data. IEEE Signal Process. Mag. 34, 18\u201342 (2017)","journal-title":"IEEE Signal Process. Mag."},{"key":"3_CR9","unstructured":"Guo, X., Wu, L., Zhao, L.: Deep graph translation. arXiv preprint arXiv:1805.09980 (2018)"},{"key":"3_CR10","doi-asserted-by":"crossref","unstructured":"Roffo, G., Melzi, S., Cristani, M.: Infinite feature selection. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 4202\u20134210 (2015)","DOI":"10.1109\/ICCV.2015.478"},{"key":"3_CR11","unstructured":"Buckner, R., et al.: The brain genomics superstruct project. Harvard Dataverse Network (2012)"},{"key":"3_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1007\/978-3-319-67159-8_7","volume-title":"Connectomics in NeuroImaging","author":"M Soussia","year":"2017","unstructured":"Soussia, M., Rekik, I.: High-order connectomic manifold learning for autistic brain state identification. In: Wu, G., Laurienti, P., Bonilha, L., Munsell, B.C. (eds.) CNI 2017. LNCS, vol. 10511, pp. 51\u201359. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-67159-8_7"},{"key":"3_CR13","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1038\/nmeth.3863","volume":"13","author":"N Samusik","year":"2016","unstructured":"Samusik, N., Good, Z., Spitzer, M.H., Davis, K.L., Nolan, G.P.: Automated mapping of phenotype space with single-cell data. Nature Methods 13, 493 (2016)","journal-title":"Nature Methods"},{"key":"3_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1007\/978-3-319-67159-8_6","volume-title":"Connectomics in NeuroImaging","author":"A Lisowska","year":"2017","unstructured":"Lisowska, A., Rekik, I.: Pairing-based ensemble classifier learning using convolutional brain multiplexes and multi-view brain networks for early dementia diagnosis. In: Wu, G., Laurienti, P., Bonilha, L., Munsell, B.C. (eds.) CNI 2017. LNCS, vol. 10511, pp. 42\u201350. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-67159-8_6"},{"key":"3_CR15","doi-asserted-by":"publisher","first-page":"747","DOI":"10.2466\/pms.107.3.747-760","volume":"107","author":"ID Cherney","year":"2008","unstructured":"Cherney, I.D., Brabec, C.M., Runco, D.V.: Mapping out spatial ability: sex differences in way-finding navigation. Percept. Motor Skills 107, 747\u2013760 (2008)","journal-title":"Percept. Motor Skills"},{"key":"3_CR16","doi-asserted-by":"publisher","first-page":"823","DOI":"10.1073\/pnas.1316909110","volume":"111","author":"M Ingalhalikar","year":"2014","unstructured":"Ingalhalikar, M., et al.: Sex differences in the structural connectome of the human brain. Proc. Nat. Acad. Sci. 111, 823\u2013828 (2014)","journal-title":"Proc. Nat. Acad. Sci."},{"key":"3_CR17","doi-asserted-by":"publisher","first-page":"953","DOI":"10.1016\/j.neuropsychologia.2004.08.007","volume":"43","author":"VJ Bourne","year":"2005","unstructured":"Bourne, V.J.: Lateralised processing of positive facial emotion: sex differences in strength of hemispheric dominance. Neuropsychologia 43, 953\u2013956 (2005)","journal-title":"Neuropsychologia"},{"key":"3_CR18","doi-asserted-by":"publisher","first-page":"107183","DOI":"10.1016\/j.patcog.2019.107183","volume":"101","author":"N Georges","year":"2020","unstructured":"Georges, N., Mhiri, I., Rekik, I.: Alzheimer\u2019s disease neuroimaging initiative and others: identifying the best data-driven feature selection method for boosting reproducibility in classification tasks. Pattern Recognit. 101, 107183 (2020)","journal-title":"Pattern Recognit."}],"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\/978-3-030-59354-4_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T22:11:56Z","timestamp":1759270316000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-59354-4_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030593537","9783030593544"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-59354-4_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"1 October 2020","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":"Lima","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Peru","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"prime2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/basira-lab.com\/prime-miccai-2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"20","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"17","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"85% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2-3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3-4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The workshop was held virtually due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}