{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T07:31:27Z","timestamp":1771659087816,"version":"3.50.1"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030908843","type":"print"},{"value":"9783030908850","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[[2021]]},"DOI":"10.1007\/978-3-030-90885-0_8","type":"book-chapter","created":{"date-parts":[[2021,11,9]],"date-time":"2021-11-09T14:04:29Z","timestamp":1636466669000},"page":"82-92","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A Novel Alcoholic EEG Signals Classification Approach Based on AdaBoost k-means Coupled with Statistical Model"],"prefix":"10.1007","author":[{"given":"Mohammed","family":"Diykh","sequence":"first","affiliation":[]},{"given":"Shahab","family":"Abdulla","sequence":"additional","affiliation":[]},{"given":"Atheer Y.","family":"Oudah","sequence":"additional","affiliation":[]},{"given":"Haydar Abdulameer","family":"Marhoon","sequence":"additional","affiliation":[]},{"given":"Siuly","family":"Siuly","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,11,10]]},"reference":[{"issue":"11","key":"8_CR1","doi-asserted-by":"publisher","first-page":"1754","DOI":"10.1016\/j.neurobiolaging.2007.04.013","volume":"29","author":"DP Pelvig","year":"2008","unstructured":"Pelvig, D.P., Pakkenberg, H., Stark, A.K., Pakkenberg, B.: Neocortical glial cell numbers in human brains. Neurobiol. Aging 29(11), 1754\u20131762 (2008)","journal-title":"Neurobiol. Aging"},{"key":"8_CR2","doi-asserted-by":"crossref","unstructured":"Deiner, S., Silverstein, J.: Postoperative delirium and cognitive dysfunction. Br. J. Anaesth. 103(suppl_1), i41\u2013i46 (2009)","DOI":"10.1093\/bja\/aep291"},{"key":"8_CR3","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1016\/j.neuropharm.2017.01.012","volume":"122","author":"ND Volkow","year":"2017","unstructured":"Volkow, N.D., Wiers, C.E., Shokri-Kojori, E., Tomasi, D., Wang, G.-J., Baler, R.: Neurochemical and metabolic effects of acute and chronic alcohol in the human brain: studies with positron emission tomography. Neuropharmacology 122, 175\u2013188 (2017)","journal-title":"Neuropharmacology"},{"issue":"16","key":"8_CR4","doi-asserted-by":"publisher","first-page":"1058","DOI":"10.1056\/NEJM199510193331607","volume":"333","author":"CS Lieber","year":"1995","unstructured":"Lieber, C.S.: Medical disorders of alcoholism. N. Engl. J. Med. 333(16), 1058\u20131065 (1995)","journal-title":"N. Engl. J. Med."},{"issue":"1","key":"8_CR5","first-page":"65","volume":"21","author":"M Oscar-Berman","year":"1997","unstructured":"Oscar-Berman, M., Shagrin, B., Evert, D.L., Epstein, C.: Impairments of brain and behavior: the neurological effects of alcohol. Alcohol Health Res. World 21(1), 65 (1997)","journal-title":"Alcohol Health Res. World"},{"key":"8_CR6","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1016\/j.yebeh.2014.10.001","volume":"41","author":"UR Acharya","year":"2014","unstructured":"Acharya, U.R., Bhat, S., Adeli, H., Adeli, A.: Computer-aided diagnosis of alcoholism-related EEG signals. Epilepsy Behav. 41, 257\u2013263 (2014)","journal-title":"Epilepsy Behav."},{"issue":"1","key":"8_CR7","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1016\/j.rbmret.2007.11.003","volume":"29","author":"O Faust","year":"2008","unstructured":"Faust, O., Acharya, R., Allen, A.R., Lin, C.: Analysis of EEG signals during epileptic and alcoholic states using AR modeling techniques. IRBM 29(1), 44\u201352 (2008)","journal-title":"IRBM"},{"key":"8_CR8","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1016\/j.asoc.2016.11.002","volume":"50","author":"S Patidar","year":"2017","unstructured":"Patidar, S., Pachori, R.B., Upadhyay, A., Acharya, U.R.: An integrated alcoholic index using tunable-Q wavelet transform based features extracted from EEG signals for diagnosis of alcoholism. Appl. Soft Comput. 50, 71\u201378 (2017)","journal-title":"Appl. Soft Comput."},{"key":"8_CR9","doi-asserted-by":"crossref","unstructured":"Shooshtari, M.A., Setarehdan, S.K.: Selection of optimal EEG channels for classification of signals correlated with alcohol abusers. In: IEEE 10th International Conference on Signals Processing, pp. 1\u20134. IEEE, Beijing (2010)","DOI":"10.1109\/ICOSP.2010.5656482"},{"key":"8_CR10","doi-asserted-by":"crossref","unstructured":"Kumar, Y., Dewal, M., Anand, R.: Features extraction of EEG signals using approximate and sample entropy. In: The 2012 IEEE Students Conference on Electrical, Electronics and Computer Science, pp. 1\u20135, IEEE, Bhopal (2012)","DOI":"10.1109\/SCEECS.2012.6184830"},{"issue":"2","key":"8_CR11","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/j.irbm.2017.02.002","volume":"38","author":"R Cao","year":"2017","unstructured":"Cao, R., Deng, H., Wu, Z., Liu, G., Guo, H., Xiang, J.: Decreased synchronization in alcoholics using EEG. IRBM 38(2), 63\u201370 (2017)","journal-title":"IRBM"},{"key":"8_CR12","unstructured":"Lin, C.-F., Yeh, S.-W., Chien, Y.-Y., Peng, T.-I., Wang, J.-H., Chang, S.-H.: A HHT-based time frequency analysis scheme for clinical alcoholic EEG signals. In: The WSEAS International Conference. Proceedings of the Mathematics and Computers in Science and Engineering, no. 9. World Scientific and Engineering Academy and Society (2009)"},{"key":"8_CR13","doi-asserted-by":"crossref","unstructured":"Kousarrizi, M.R.N., Ghanbari, A.A., Gharaviri, A., Teshnehlab, M., Aliyari, M.: Classification of alcoholics and non-alcoholics via EEG using SVM and neural networks. In: 3rd International Conference on Bioinformatics and Biomedical Engineering, pp. 1\u20134, Beijing. IEEE (2009)","DOI":"10.1109\/ICBBE.2009.5162504"},{"key":"8_CR14","doi-asserted-by":"publisher","unstructured":"Sadiq, M.T., Yu, X., Yuan, Z., Aziz, M.Z., Siuly, S., Ding, W.: A matrix determinant feature extraction approach for decoding motor and mental imagery EEG in subject specific tasks. IEEE Trans. Cogn. Dev. Syst. (2020). https:\/\/doi.org\/10.1109\/TCDS.2020.3040438","DOI":"10.1109\/TCDS.2020.3040438"},{"key":"8_CR15","doi-asserted-by":"crossref","unstructured":"Sadiq, M.T., Yu, X., Yuan, Z.: Exploiting dimensionality reduction and neural network techniques for the development of expert brain\u2013computer interfaces. Expert Syst. Appl. 164, 114031 (2020)","DOI":"10.1016\/j.eswa.2020.114031"},{"key":"8_CR16","unstructured":"Hettich, S., Bay, S.: The UCI KDD Archive. University of California, Irvine, CA. Department of Information and Computer Science 152 (1999). http:\/\/kdd.ics.uci.edu"},{"issue":"12","key":"8_CR17","doi-asserted-by":"publisher","first-page":"1157","DOI":"10.1016\/S0006-3223(96)00552-5","volume":"42","author":"XL Zhang","year":"1997","unstructured":"Zhang, X.L., Begleiter, H., Porjesz, B., Litke, A.: Electrophysiological evidence of memory impairment in alcoholic patients. Biol. Psychiat. 42(12), 1157\u20131171 (1997)","journal-title":"Biol. Psychiat."},{"key":"8_CR18","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/j.eswa.2017.08.012","volume":"90","author":"M Diykh","year":"2017","unstructured":"Diykh, M., Li, Y., Wen, P.: Classify epileptic EEG signals using weighted complex networks-based community structure detection. Expert Syst. Appl. 90, 87\u2013100 (2017)","journal-title":"Expert Syst. Appl."},{"key":"8_CR19","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1016\/j.measurement.2018.01.024","volume":"119","author":"M Diykh","year":"2018","unstructured":"Diykh, M., Li, Y., Wen, P., Li, T.: Complex networks approach for depth of anesthesia assessment. Measurement 119, 178\u2013189 (2018)","journal-title":"Measurement"},{"issue":"1","key":"8_CR20","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1049\/iet-smt.2018.5393","volume":"14","author":"M Diykh","year":"2019","unstructured":"Diykh, M., Miften, F.S., Abdulla, S., Saleh, K., Green, J.H.: Robust approach to depth of anaesthesia assessment based on hybrid transform and statistical features. IET Sci. Meas. Technol. 14(1), 128\u2013136 (2019)","journal-title":"IET Sci. Meas. Technol."},{"key":"8_CR21","doi-asserted-by":"publisher","first-page":"102005","DOI":"10.1016\/j.artmed.2020.102005","volume":"112","author":"FS Miften","year":"2021","unstructured":"Miften, F.S., Diykh, M., Abdulla, S., Siuly, S., Green, J.H., Deo, R.C.: A new framework for classification of multi-category hand grasps using EMG signals. Artif. Intell. Med. 112, 102005 (2021)","journal-title":"Artif. Intell. Med."},{"issue":"03","key":"8_CR22","doi-asserted-by":"publisher","first-page":"1350033","DOI":"10.1142\/S0219519413500334","volume":"13","author":"O Faust","year":"2013","unstructured":"Faust, O., Yu, W., Kadri, N.A.: Computer-based identification of normal and alcoholic EEG signals using wavelet packets and energy measures. J. Mech. Med. Biol. 13(03), 1350033 (2013)","journal-title":"J. Mech. Med. Biol."},{"issue":"2","key":"8_CR23","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1166\/jmihi.2013.1170","volume":"3","author":"O Faust","year":"2013","unstructured":"Faust, O., Yanti, R., Yu, W.: Automated detection of alcohol related changes in electroencephalograph signals. J. Med. Imaging Health Inform. 3(2), 333\u2013339 (2013)","journal-title":"J. Med. Imaging Health Inform."},{"issue":"1","key":"8_CR24","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.cmpb.2005.06.005","volume":"80","author":"N Kannathal","year":"2005","unstructured":"Kannathal, N., Acharya, U.R., Lim, C.M., Sadasivan, P.: Characterization of EEG\u2014a comparative study. Comput. Methods Programs Biomed. 80(1), 17\u201323 (2005)","journal-title":"Comput. Methods Programs Biomed."}],"container-title":["Lecture Notes in Computer Science","Health Information Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-90885-0_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T20:37:58Z","timestamp":1726087078000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-90885-0_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030908843","9783030908850"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-90885-0_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"10 November 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Health Information Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Melbourne, VIC","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 October 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"his22021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/his-conferences.org\/2021\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"56","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":"16","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":"7","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":"29% - 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":"5","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)"}}]}}