{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T20:10:54Z","timestamp":1743106254173,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031208362"},{"type":"electronic","value":"9783031208379"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[[2022]]},"DOI":"10.1007\/978-3-031-20837-9_13","type":"book-chapter","created":{"date-parts":[[2022,11,25]],"date-time":"2022-11-25T09:12:17Z","timestamp":1669367537000},"page":"158-169","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["RF-Isolation: A Novel Representation of\u00a0Structural Connectivity Networks for\u00a0Multiple Sclerosis Classification"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9468-5298","authenticated-orcid":false,"given":"Antonella","family":"Mensi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1641-186X","authenticated-orcid":false,"given":"Simona","family":"Schiavi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria","family":"Petracca","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicole","family":"Graziano","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alessandro","family":"Daducci","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matilde","family":"Inglese","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manuele","family":"Bicego","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,11,26]]},"reference":[{"key":"13_CR1","doi-asserted-by":"publisher","unstructured":"Bester, M., Petracca, M., Inglese, M.: Neuroimaging of multiple sclerosis, acute disseminated encephalomyelitis, and other demyelinating diseases. In: Seminars in Roentgenology, vol. 49, pp. 76\u201385 (2013). https:\/\/doi.org\/10.1053\/j.ro.2013.09.002","DOI":"10.1053\/j.ro.2013.09.002"},{"key":"13_CR2","doi-asserted-by":"publisher","unstructured":"Bicego, M.: Dissimilarity random forest clustering. In: 2020 IEEE ICDM, pp. 936\u2013941 (2020). https:\/\/doi.org\/10.1109\/ICDM50108.2020.00105","DOI":"10.1109\/ICDM50108.2020.00105"},{"issue":"1","key":"13_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12864-019-6413-7","volume":"21","author":"D Chicco","year":"2020","unstructured":"Chicco, D., Jurman, G.: The advantages of the Matthews correlation coefficient (mcc) over f1 score and accuracy in binary classification evaluation. BMC Genomics 21(1), 1\u201313 (2020). https:\/\/doi.org\/10.1186\/s12864-019-6413-7","journal-title":"BMC Genomics"},{"issue":"1","key":"13_CR4","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1109\/TMI.2014.2352414","volume":"34","author":"A Daducci","year":"2014","unstructured":"Daducci, A., Dal Pal\u00f9, A., Lemkaddem, A., Thiran, J.P.: COMMIT: convex optimization modeling for microstructure informed tractography. IEEE Trans. Med. Imaging 34(1), 246\u2013257 (2014). https:\/\/doi.org\/10.1109\/TMI.2014.2352414","journal-title":"IEEE Trans. Med. Imaging"},{"key":"13_CR5","first-page":"1","volume":"7","author":"J Dem\u0161ar","year":"2006","unstructured":"Dem\u0161ar, J.: Statistical comparisons of classifiers over multiple data sets. J. Mach. Learn. Res. 7, 1\u201330 (2006)","journal-title":"J. Mach. Learn. Res."},{"issue":"3","key":"13_CR6","doi-asserted-by":"publisher","first-page":"968","DOI":"10.1016\/j.neuroimage.2006.01.021","volume":"31","author":"RS Desikan","year":"2006","unstructured":"Desikan, R.S., et al.: An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31(3), 968\u2013980 (2006). https:\/\/doi.org\/10.1016\/j.neuroimage.2006.01.021","journal-title":"Neuroimage"},{"key":"13_CR7","unstructured":"Knuth, D.E.: The art of computer programming. Sorting Search. 3, Ch\u20136 (1973)"},{"issue":"1","key":"13_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2133360.2133363","volume":"6","author":"FT Liu","year":"2012","unstructured":"Liu, F.T., Ting, K.M., Zhou, Z.H.: Isolation-based anomaly detection. ACM Trans. Knowl. Discov. Data 6(1), 1\u201339 (2012). https:\/\/doi.org\/10.1145\/2133360.2133363","journal-title":"ACM Trans. Knowl. Discov. Data"},{"key":"13_CR9","doi-asserted-by":"publisher","unstructured":"Mensi, A., Bicego, M., Tax, D.M.: Proximity isolation forests. In: 2020 25th ICPR, pp. 8021\u20138028. IEEE (2021). https:\/\/doi.org\/10.1109\/ICPR48806.2021.9412322","DOI":"10.1109\/ICPR48806.2021.9412322"},{"key":"13_CR10","doi-asserted-by":"crossref","unstructured":"Noshad, M., Moon, K.R., Sekeh, S.Y., Hero, A.O.: Direct estimation of information divergence using nearest neighbor ratios. In: 2017 IEEE International Symposium on Information Theory (ISIT), pp. 903\u2013907. IEEE (2017)","DOI":"10.1109\/ISIT.2017.8006659"},{"issue":"2","key":"13_CR11","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1177\/1352458518820759","volume":"26","author":"E Pagani","year":"2020","unstructured":"Pagani, E., et al.: Structural connectivity in multiple sclerosis and modeling of disconnection. Mult. Scler. J. 26(2), 220\u2013232 (2020). https:\/\/doi.org\/10.1177\/1352458518820759","journal-title":"Mult. Scler. J."},{"issue":"1","key":"13_CR12","first-page":"6673","volume":"18","author":"P Probst","year":"2017","unstructured":"Probst, P., Boulesteix, A.L.: To tune or not to tune the number of trees in random forest. J. Mach. Learn. Res. 18(1), 6673\u20136690 (2017)","journal-title":"J. Mach. Learn. Res."},{"issue":"3","key":"13_CR13","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). https:\/\/doi.org\/10.1016\/j.neuroimage.2009.10.003","journal-title":"Neuroimage"},{"key":"13_CR14","doi-asserted-by":"publisher","DOI":"10.1111\/jon.12991","author":"S Schiavi","year":"2022","unstructured":"Schiavi, S., et al.: Classification of multiple sclerosis patients based on structural disconnection: a robust feature selection approach. J. Neuroimaging (2022). https:\/\/doi.org\/10.1111\/jon.12991","journal-title":"J. Neuroimaging"},{"issue":"11","key":"13_CR15","doi-asserted-by":"publisher","first-page":"2951","DOI":"10.1002\/hbm.24989","volume":"41","author":"S Schiavi","year":"2020","unstructured":"Schiavi, S., et al.: Sensory-motor network topology in multiple sclerosis: structural connectivity analysis accounting for intrinsic density discrepancy. Hum. Brain Mapp. 41(11), 2951\u20132963 (2020). https:\/\/doi.org\/10.1002\/hbm.24989","journal-title":"Hum. Brain Mapp."}],"container-title":["Lecture Notes in Computer Science","Computational Intelligence Methods for Bioinformatics and Biostatistics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-20837-9_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,25]],"date-time":"2022-11-25T09:20:42Z","timestamp":1669368042000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-20837-9_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031208362","9783031208379"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-20837-9_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"26 November 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CIBB","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 November 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 November 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cibb2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.isa.cnr.it\/cibb2021\/","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":"EquinOCS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"26","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":"19","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":"0","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":"73% - 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":"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":"2","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}