{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T20:00:31Z","timestamp":1742932831965,"version":"3.40.3"},"publisher-location":"Cham","reference-count":37,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030948757"},{"type":"electronic","value":"9783030948764"}],"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\/978-3-030-94876-4_14","type":"book-chapter","created":{"date-parts":[[2022,1,18]],"date-time":"2022-01-18T08:20:02Z","timestamp":1642494002000},"page":"198-209","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Early Detection of Parkinson\u2019s Disease as a Pre-diagnosis Tool Using Various Classification Techniques on Vocal Features"],"prefix":"10.1007","author":[{"family":"Vaibhaw","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pratik","family":"Behera","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vaibhav","family":"Bal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jay","family":"Sarraf","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,1,17]]},"reference":[{"issue":"3","key":"14_CR1","doi-asserted-by":"publisher","first-page":"276","DOI":"10.1212\/WNL.0b013e31827deb74","volume":"80","author":"TK Khoo","year":"2013","unstructured":"Khoo, T.K., et al.: The spectrum of nonmotor symptoms in early Parkinson disease. Neurology 80(3), 276\u2013281 (2013)","journal-title":"Neurology"},{"issue":"4","key":"14_CR2","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1212\/01.wnl.0000266593.50534.e8","volume":"69","author":"D Verbaan","year":"2007","unstructured":"Verbaan, D., Marinus, J., Visser, M., van Rooden, S.M., Stiggelbout, A.M., van Hilten, J.J.: Patient-reported autonomic symptoms in Parkinson disease. Neurology 69(4), 333\u2013341 (2007)","journal-title":"Neurology"},{"issue":"6","key":"14_CR3","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1038\/nrneurol.2012.80","volume":"8","author":"RL Doty","year":"2012","unstructured":"Doty, R.L.: Olfactory dysfunction in Parkinson disease. Nat. Rev. Neurol. 8(6), 329\u2013339 (2012)","journal-title":"Nat. Rev. Neurol."},{"issue":"12","key":"14_CR4","doi-asserted-by":"publisher","first-page":"856","DOI":"10.3949\/ccjm.75a.07005","volume":"75","author":"M Pandya","year":"2008","unstructured":"Pandya, M., Kubu, C.S., Giroux, M.L.: Parkinson disease: not just a movement disorder. Clevel. Clin. J. Med. 75(12), 856\u2013864 (2008)","journal-title":"Clevel. Clin. J. Med."},{"issue":"6","key":"14_CR5","doi-asserted-by":"publisher","first-page":"548","DOI":"10.1001\/jama.2019.22360","volume":"323","author":"MJ Armstrong","year":"2020","unstructured":"Armstrong, M.J., Okun, M.S.: Diagnosis and treatment of Parkinson disease: a review. JAMA 323(6), 548\u2013560 (2020)","journal-title":"JAMA"},{"issue":"11","key":"14_CR6","doi-asserted-by":"publisher","first-page":"804","DOI":"10.1038\/nrd.2018.136","volume":"17","author":"D Charvin","year":"2018","unstructured":"Charvin, D., Medori, R., Hauser, R.A., Rascol, O.: Therapeutic strategies for Parkinson disease: beyond dopaminergic drugs. Nat. Rev. Drug Discov. 17(11), 804\u2013822 (2018)","journal-title":"Nat. Rev. Drug Discov."},{"issue":"2","key":"14_CR7","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1016\/j.bcp.2007.01.036","volume":"74","author":"KS Rommelfanger","year":"2007","unstructured":"Rommelfanger, K.S., Weinshenker, D.: Norepinephrine: the redheaded stepchild of Parkinson\u2019s disease. Biochem. Pharmacol. 74(2), 177\u2013190 (2007)","journal-title":"Biochem. Pharmacol."},{"issue":"1","key":"14_CR8","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1212\/WNL.37.1.42","volume":"37","author":"R Cash","year":"1987","unstructured":"Cash, R., Dennis, T., L\u2019Heureux, R., Raisman, R., Javoy-Agid, F., Scatton, B.: Parkinson\u2019s disease and dementia: norepinephrine and dopamine in locus ceruleus. Neurology 37(1), 42 (1987)","journal-title":"Neurology"},{"issue":"5","key":"14_CR9","doi-asserted-by":"publisher","first-page":"338","DOI":"10.7326\/0003-4819-133-5-200009050-00009","volume":"133","author":"DS Goldstein","year":"2000","unstructured":"Goldstein, D.S., Holmes, C., Li, S.T., Bruce, S., Metman, L.V., Cannon III,   R.O.: Cardiac sympathetic denervation in Parkinson disease. Ann. Intern. Med. 133(5), 338\u2013347 (2000)","journal-title":"Ann. Intern. Med."},{"key":"14_CR10","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1016\/j.parkreldis.2017.10.003","volume":"52","author":"DS Goldstein","year":"2018","unstructured":"Goldstein, D.S., Holmes, C., Lopez, G.J., Wu, T., Sharabi, Y.: Cardiac sympathetic denervation predicts PD in at-risk individuals. Parkinsonism Relat. Disord. 52, 90\u201393 (2018)","journal-title":"Parkinsonism Relat. Disord."},{"issue":"3","key":"14_CR11","doi-asserted-by":"publisher","first-page":"372","DOI":"10.1002\/mds.27344","volume":"33","author":"JA Palma","year":"2018","unstructured":"Palma, J.A., Kaufmann, H.: Treatment of autonomic dysfunction in Parkinson disease and other synucleinopathies. Mov. Disord. 33(3), 372\u2013390 (2018)","journal-title":"Mov. Disord."},{"key":"14_CR12","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1016\/j.arr.2017.12.007","volume":"42","author":"H Deng","year":"2018","unstructured":"Deng, H., Wang, P., Jankovic, J.: The genetics of Parkinson disease. Ageing Res. Rev. 42, 72\u201385 (2018)","journal-title":"Ageing Res. Rev."},{"issue":"5","key":"14_CR13","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1016\/j.tem.2018.02.006","volume":"29","author":"SM Ostojic","year":"2018","unstructured":"Ostojic, S.M.: Inadequate production of H2 by gut microbiota and Parkinson disease. Trends Endocrinol. Metab. 29(5), 286\u2013288 (2018)","journal-title":"Trends Endocrinol. Metab."},{"key":"14_CR14","doi-asserted-by":"publisher","first-page":"S30","DOI":"10.1016\/j.parkreldis.2017.07.033","volume":"46","author":"DW Dickson","year":"2018","unstructured":"Dickson, D.W.: Neuropathology of Parkinson disease. Parkinsonism Relat. Disord. 46, S30\u2013S33 (2018)","journal-title":"Parkinsonism Relat. Disord."},{"key":"14_CR15","doi-asserted-by":"crossref","unstructured":"Poewe, W., et al.: Parkinson disease. Nat. Rev. Dis. Primers 3(1), 1\u201321 (2017)","DOI":"10.1038\/nrdp.2017.13"},{"key":"14_CR16","doi-asserted-by":"crossref","unstructured":"Moro-Velazquez, L., Gomez-Garcia, J.A., Arias-Londo\u00f1o, J.D., Dehak, N., Godino-Llorente, J.I.: Advances in Parkinson\u2019s Disease detection and assessment using voice and speech: a review of the articulatory and phonatory aspects. Biomed. Sig. Process. Control 66, 102418 (2021)","DOI":"10.1016\/j.bspc.2021.102418"},{"issue":"1","key":"14_CR17","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/j.bbe.2020.12.009","volume":"41","author":"T Zhang","year":"2021","unstructured":"Zhang, T., Zhang, Y., Sun, H., Shan, H.: Parkinson disease detection using energy direction features based on EMD from voice signal. Biocybern. Biomed. Eng. 41(1), 127\u2013141 (2021)","journal-title":"Biocybern. Biomed. Eng."},{"issue":"3","key":"14_CR18","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s00702-017-1676-0","volume":"124","author":"L Brabenec","year":"2017","unstructured":"Brabenec, L., Mekyska, J., Galaz, Z., Rektorova, I.: Speech disorders in Parkinson\u2019s disease: early diagnostics and effects of medication and brain stimulation. J. Neural Transm. 124(3), 303\u2013334 (2017). https:\/\/doi.org\/10.1007\/s00702-017-1676-0","journal-title":"J. Neural Transm."},{"key":"14_CR19","doi-asserted-by":"crossref","unstructured":"Soumaya, Z., Taoufiq, B.D., Benayad, N., Yunus, K., Abdelkrim, A.: The detection of Parkinson disease using the genetic algorithm and SVM classifier. Appl. Acous.\u00a0171, 107528 (2021)","DOI":"10.1016\/j.apacoust.2020.107528"},{"key":"14_CR20","unstructured":"Johri, A., Tripathi, A.: Parkinson disease detection using deep neural networks. In: 2019 Twelfth International Conference on Contemporary Computing (IC3),\u00a0pp. 1\u20134. IEEE, August 2019"},{"key":"14_CR21","doi-asserted-by":"crossref","unstructured":"Senturk, Z.K.: Early diagnosis of Parkinson\u2019s disease using machine learning algorithms. Med. Hypotheses 138, 109603 (2020)","DOI":"10.1016\/j.mehy.2020.109603"},{"key":"14_CR22","doi-asserted-by":"crossref","unstructured":"Abdurrahman, G., Sintawati, M.: Implementation of xgboost for classification of Parkinson\u2019s disease. J. Phys. Conf. Ser. 1538(1), 012024 (2020)","DOI":"10.1088\/1742-6596\/1538\/1\/012024"},{"issue":"1","key":"14_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12911-020-01250-7","volume":"20","author":"I Karabayir","year":"2020","unstructured":"Karabayir, I., Goldman, S.M., Pappu, S., Akbilgic, O.: Gradient boosting for Parkinson\u2019s disease diagnosis from voice recordings. BMC Med. Inform. Decis. Mak. 20(1), 1\u20137 (2020)","journal-title":"BMC Med. Inform. Decis. Mak."},{"key":"14_CR24","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1016\/j.cmpb.2017.02.019","volume":"142","author":"L Naranjo","year":"2017","unstructured":"Naranjo, L., Perez, C.J., Martin, J., Campos-Roca, Y.: A two-stage variable selection and classification approach for Parkinson\u2019s disease detection by using voice recording replications. Comput. Methods Programs Biomed. 142, 147\u2013156 (2017)","journal-title":"Comput. Methods Programs Biomed."},{"key":"14_CR25","doi-asserted-by":"crossref","unstructured":"Olanrewaju, R.F., Sahari, N.S., Musa, A.A., Hakiem, N.: Application of neural networks in early detection and diagnosis of Parkinson\u2019s disease. In: 2014 International Conference on Cyber and IT Service Management (CITSM),\u00a0pp. 78\u201382. IEEE, November 2014","DOI":"10.1109\/CITSM.2014.7042180"},{"key":"14_CR26","doi-asserted-by":"crossref","unstructured":"Little, M., McSharry, P., Hunter, E., Spielman, J., Ramig, L.: Suitability of dysphonia measurements for telemonitoring of Parkinson\u2019s disease. IEEE Trans. Biomed. Eng. 56(4) (2008)","DOI":"10.1109\/TBME.2008.2005954"},{"key":"14_CR27","doi-asserted-by":"crossref","unstructured":"Patro, S., Sahu, K.K.: Normalization: a preprocessing stage (2015). arXiv preprint arXiv:1503.06462","DOI":"10.17148\/IARJSET.2015.2305"},{"key":"14_CR28","doi-asserted-by":"crossref","unstructured":"Saeys, Y., Inza, I., Larranaga, P.: A review of feature selection techniques in bioinformatics. Bioinformatics 23(19), 2507\u20132517 (2007)","DOI":"10.1093\/bioinformatics\/btm344"},{"key":"14_CR29","unstructured":"Guyon, I., Elisseeff, A.: An introduction to variable and feature selection. J. Mach. Learn. Res. 3(March), 1157\u20131182 (2003)"},{"key":"14_CR30","unstructured":"Chen, T., He, T., Benesty, M., Khotilovich, V., Tang, Y., Cho, H.: Xgboost: extreme gradient boosting. R package version 0.4-2 1(4) (2015)"},{"key":"14_CR31","doi-asserted-by":"crossref","unstructured":"Chen, T., Guestrin, C.: XGBoost: a scalable tree boosting system. In:\u00a0Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,\u00a0pp. 785\u2013794, August, 2016","DOI":"10.1145\/2939672.2939785"},{"key":"14_CR32","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1007\/978-3-540-72903-7_35","volume-title":"Graph-Based Representations in Pattern Recognition","author":"K Riesen","year":"2007","unstructured":"Riesen, K., Neuhaus, M., Bunke, H.: Graph embedding in vector spaces by means of prototype selection. In: Escolano, F., Vento, M. (eds.) GbRPR 2007. LNCS, vol. 4538, pp. 383\u2013393. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-72903-7_35"},{"issue":"12","key":"14_CR33","doi-asserted-by":"publisher","first-page":"1565","DOI":"10.1038\/nbt1206-1565","volume":"24","author":"WS Noble","year":"2006","unstructured":"Noble, W.S.: What is a support vector machine? Nat. Biotechnol. 24(12), 1565\u20131567 (2006)","journal-title":"Nat. Biotechnol."},{"key":"14_CR34","doi-asserted-by":"crossref","unstructured":"Doll\u00e1r, P., Zitnick, C.L.: Structured forests for fast edge detection. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1841\u20131848 (2013)","DOI":"10.1109\/ICCV.2013.231"},{"key":"14_CR35","doi-asserted-by":"crossref","unstructured":"Breiman, L. Random forests. Mach. Learn. 45(1), 5\u201332 (2001)","DOI":"10.1023\/A:1010933404324"},{"key":"14_CR36","doi-asserted-by":"publisher","first-page":"278","DOI":"10.1016\/j.neucom.2017.08.040","volume":"275","author":"W Cao","year":"2018","unstructured":"Cao, W., Wang, X., Ming, Z., Gao, J.: A review on neural networks with random weights. Neurocomputing 275, 278\u2013287 (2018)","journal-title":"Neurocomputing"},{"key":"14_CR37","unstructured":"Cilimkovic, M.: Neural Networks And Back Propagation Algorithm, vol. 15, pp. 1\u201312. Institute of Technology Blanchardstown, Dublin (2015)"}],"container-title":["Lecture Notes in Computer Science","Distributed Computing and Intelligent Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-94876-4_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,18]],"date-time":"2022-01-18T08:23:49Z","timestamp":1642494229000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-94876-4_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030948757","9783030948764"],"references-count":37,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-94876-4_14","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":"17 January 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICDCIT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Distributed Computing and Internet Technology","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bhubaneswar","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 January 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 January 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icdcit2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.icdcit.ac.in\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"50","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":"11","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":"4","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":"22% - 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":"3.2","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":"2.7","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)"}},{"value":"Additionally, 4 invited papers are included.","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)"}}]}}