{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T22:40:38Z","timestamp":1742942438396,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030344818"},{"type":"electronic","value":"9783030344825"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","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":[[2019]]},"DOI":"10.1007\/978-3-030-34482-5_10","type":"book-chapter","created":{"date-parts":[[2019,11,20]],"date-time":"2019-11-20T12:03:12Z","timestamp":1574251392000},"page":"106-113","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Comprehensive Database Based on Multiple Data Sources to Facilitate Diagnosis of ASD"],"prefix":"10.1007","author":[{"given":"Tao","family":"Chen","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,12,2]]},"reference":[{"issue":"8","key":"10_CR1","doi-asserted-by":"publisher","first-page":"921","DOI":"10.1097\/CHI.0b013e318179964f","volume":"47","author":"E Simonoff","year":"2008","unstructured":"Simonoff, E., et al.: Psychiatric disorders in children with autism spectrum disorders: prevalence, comorbidity, and associated factors in a population-derived sample. J. Am. Acad. Child Adolesc. Psychiatry 47(8), 921\u2013929 (2008)","journal-title":"J. Am. Acad. Child Adolesc. Psychiatry"},{"key":"10_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/B0-12-226870-9\/01070-4","volume-title":"Diagnostic and Statistical Manual of Mental Disorders (DSM-IV)","author":"RJ Hu","year":"2003","unstructured":"Hu, R.J.: Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). Academic Press, New York (2003)"},{"issue":"5","key":"10_CR3","doi-asserted-by":"publisher","first-page":"693","DOI":"10.1007\/s10803-008-0674-3","volume":"39","author":"K Gotham","year":"2009","unstructured":"Gotham, K., Pickles, A., Lord, C.: Standardizing ADOS scores for a measure of severity in autism spectrum disorders. J. Autism Dev. Disord. 39(5), 693\u2013705 (2009)","journal-title":"J. Autism Dev. Disord."},{"issue":"5","key":"10_CR4","doi-asserted-by":"publisher","first-page":"719","DOI":"10.1111\/1469-7610.00488","volume":"40","author":"A Cox","year":"1999","unstructured":"Cox, A., et al.: Autism spectrum disorders at 20 and 42 months of age: stability of clinical and ADI-R diagnosis. J. Child Psychol. Psychiatry 40(5), 719\u2013732 (1999)","journal-title":"J. Child Psychol. Psychiatry"},{"issue":"Pt 8","key":"10_CR5","doi-asserted-by":"publisher","first-page":"1811","DOI":"10.1093\/brain\/awh199","volume":"127","author":"MA Just","year":"2004","unstructured":"Just, M.A., Cherkassky, V.L., Keller, T.A., Minshew, N.J.: Cortical activation and synchronization during sentence comprehension in high-functioning autism: evidence of underconnectivity. Brain J. Neurol. 127(Pt 8), 1811\u20131821 (2004)","journal-title":"Brain J. Neurol."},{"key":"10_CR6","doi-asserted-by":"crossref","unstructured":"McFadden, K., Minshew, N.J.: Evidence for dysregulation of axonal growth and guidance in the etiology of ASD. Front. Hum. Neurosci. 7, 671 (2013)","DOI":"10.3389\/fnhum.2013.00671"},{"issue":"34","key":"10_CR7","doi-asserted-by":"publisher","first-page":"11199","DOI":"10.1523\/JNEUROSCI.1366-14.2014","volume":"34","author":"A. Y. Qureshi","year":"2014","unstructured":"Qureshi, A.Y., et al.: Opposing brain differences in 16p11.2 deletion and duplication carriers. J. Neurosci. Off. J. Soc. Neurosci. 34(34), 11199\u201311211 (2014)","journal-title":"Journal of Neuroscience"},{"issue":"6","key":"10_CR8","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1089\/brain.2011.0064","volume":"1","author":"EL Dennis","year":"2011","unstructured":"Dennis, E.L., et al.: Altered structural brain connectivity in healthy carriers of the autism risk gene, CNTNAP2. Brain Connect. 1(6), 447\u2013459 (2011)","journal-title":"Brain Connect."},{"issue":"5","key":"10_CR9","doi-asserted-by":"publisher","first-page":"904","DOI":"10.1016\/j.neuron.2012.07.010","volume":"75","author":"JD Rudie","year":"2012","unstructured":"Rudie, J.D., et al.: Autism-associated promoter variant in MET impacts functional and structural brain networks. Neuron 75(5), 904\u2013915 (2012)","journal-title":"Neuron"},{"issue":"7","key":"10_CR10","doi-asserted-by":"publisher","first-page":"748","DOI":"10.1176\/appi.ajp.2010.09091379","volume":"167","author":"T Insel","year":"2010","unstructured":"Insel, T., et al.: Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. Am. J. Psychiatry 167(7), 748\u2013751 (2010)","journal-title":"Am. J. Psychiatry"},{"issue":"2","key":"10_CR11","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1007\/s40273-015-0331-6","volume":"34","author":"N Payakachat","year":"2016","unstructured":"Payakachat, N., Tilford, J.M., Ungar, W.J.: National Database for Autism Research (NDAR): big data opportunities for health services research and health technology assessment. Pharm. Econ. 34(2), 127\u2013138 (2016)","journal-title":"Pharm. Econ."},{"key":"10_CR12","doi-asserted-by":"crossref","unstructured":"Buxbaum, J.D., et al.: The autism simplex collection: an international, expertly phenotyped autism sample for genetic and phenotypic analyses. Molecular autism 534 (2014)","DOI":"10.1186\/2040-2392-5-34"},{"issue":"2","key":"10_CR13","doi-asserted-by":"publisher","first-page":"463","DOI":"10.1086\/321292","volume":"69","author":"DH Geschwind","year":"2001","unstructured":"Geschwind, D.H., et al.: The autism genetic resource exchange: a resource for the study of autism and related neuropsychiatric conditions. Am. J. Hum. Genet. 69(2), 463\u2013466 (2001)","journal-title":"Am. J. Hum. Genet."},{"issue":"6","key":"10_CR14","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1038\/mp.2013.78","volume":"19","author":"A Di Martino","year":"2014","unstructured":"Di Martino, A., et al.: The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Mol. Psychiatry 19(6), 659\u2013667 (2014)","journal-title":"Mol. Psychiatry"},{"issue":"1","key":"10_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-014-0007-7","volume":"2","author":"MM Najafabadi","year":"2015","unstructured":"Najafabadi, M.M., Villanustre, F., Khoshgoftaar, T.M., Seliya, N., Wald, R., Muharemagic, E.: Deep learning applications and challenges in big data analytics. J. Big Data 2(1), 1 (2015)","journal-title":"J. Big Data"},{"issue":"1","key":"10_CR16","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1186\/s12864-019-5546-z","volume":"20","author":"H Yu","year":"2019","unstructured":"Yu, H., Samuels, D.C., Zhao, Y.Y., Guo, Y.: Architectures and accuracy of artificial neural network for disease classification from omics data. BMC Genom. 20(1), 167 (2019)","journal-title":"BMC Genom."},{"issue":"3","key":"10_CR17","first-page":"273","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20(3), 273\u2013297 (1995)","journal-title":"Mach. Learn."},{"issue":"13","key":"10_CR18","doi-asserted-by":"publisher","first-page":"i412","DOI":"10.1093\/bioinformatics\/bty239","volume":"34","author":"A Rahimi","year":"2018","unstructured":"Rahimi, A., Gonen, M.: Discriminating early- and late-stage cancers using multiple kernel learning on gene sets. Bioinformatics 34(13), i412\u2013i421 (2018)","journal-title":"Bioinformatics"},{"issue":"3","key":"10_CR19","doi-asserted-by":"publisher","first-page":"200","DOI":"10.3390\/genes10030200","volume":"10","author":"Mingxin Tao","year":"2019","unstructured":"Tao, M., et al.: Classifying breast cancer subtypes using multiple kernel learning based on omics data. Genes 10(3) (2019)","journal-title":"Genes"},{"key":"10_CR20","unstructured":"Rakotomamonjy, A., Bach, F., Canu, S., Grandvalet, Y.: SimpleMKL. J. Mach. Learn. Res. 9(11) (2008)"},{"key":"10_CR21","unstructured":"Bach, F.: Consistency of the group Lasso and multiple kernel learning. Comput. Sci. (2007)"}],"container-title":["Lecture Notes in Computer Science","Smart Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-34482-5_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T15:44:39Z","timestamp":1709826279000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-34482-5_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030344818","9783030344825"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-34482-5_10","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":"2 December 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICSH","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Smart Health","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":"1 July 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 July 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icsh2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2019.icshconf.org\/","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":"Conferency.com","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"43","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":"34","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":"34","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":"79% - 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":"4","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":"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)"}}]}}