{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T16:13:10Z","timestamp":1744215190798,"version":"3.28.0"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,10,17]],"date-time":"2020-10-17T00:00:00Z","timestamp":1602892800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,10,17]],"date-time":"2020-10-17T00:00:00Z","timestamp":1602892800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,10,17]],"date-time":"2020-10-17T00:00:00Z","timestamp":1602892800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,10,17]]},"DOI":"10.1109\/cisp-bmei51763.2020.9263641","type":"proceedings-article","created":{"date-parts":[[2020,11,25]],"date-time":"2020-11-25T22:28:41Z","timestamp":1606343321000},"page":"669-674","source":"Crossref","is-referenced-by-count":4,"title":["Epileptic Seizure Prediction from the Scalp EEG Signals by using Random Forest Algorithm"],"prefix":"10.1109","author":[{"given":"Ziyu","family":"Hu","sequence":"first","affiliation":[{"name":"Tianjin University of Technology and Education,Tianjin Key Laboratory of Information Sensing & Intelligent Control, School of Automation and Electrical Engineering,China,300222"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunxiao","family":"Han","sequence":"additional","affiliation":[{"name":"Tianjin University of Technology and Education,Tianjin Key Laboratory of Information Sensing & Intelligent Control, School of Automation and Electrical Engineering,China,300222"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fengjuan","family":"Guo","sequence":"additional","affiliation":[{"name":"Tianjin University of Technology and Education,Tianjin Key Laboratory of Information Sensing & Intelligent Control, School of Automation and Electrical Engineering,China,300222"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qing","family":"Qin","sequence":"additional","affiliation":[{"name":"Tianjin University of Technology and Education,Tianjin Key Laboratory of Information Sensing & Intelligent Control, School of Automation and Electrical Engineering,China,300222"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shanshan","family":"Li","sequence":"additional","affiliation":[{"name":"Tianjin University of Technology and Education,Tianjin Key Laboratory of Information Sensing & Intelligent Control, School of Automation and Electrical Engineering,China,300222"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingmei","family":"Qin","sequence":"additional","affiliation":[{"name":"Tianjin University of Technology and Education,Tianjin Key Laboratory of Information Sensing & Intelligent Control, School of Automation and Electrical Engineering,China,300222"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"crossref","first-page":"795","DOI":"10.3233\/THC-161225","article-title":"Prediction of epileptic seizures based on heart rate variability","volume":"24","author":"behbahani","year":"2016","journal-title":"echnology and Health Care"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-016-0579-1"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1515\/bmt-2019-0098"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s13246-019-00806-w"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.brs.2019.09.006"},{"key":"ref15","first-page":"975","article-title":"Application of machine learning to epileptic seizure detection","author":"shoeb","year":"2010","journal-title":"Proceedings of the 27th International Conference on Machine Learning (ICML-10)"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2018.04.018"},{"key":"ref17","first-page":"276","article-title":"Statistical decision-tree models for parsing, Proceedings of the 33rd annual meeting on Association for Computational Linguistics","author":"magerman","year":"1995","journal-title":"Association for Computational Linguistics"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2019.105793"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1080\/01431160412331269698"},{"key":"ref4","first-page":"107898","article-title":"Seizure prediction and intervention","author":"meisel","year":"2019","journal-title":"Neuropharmacology"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/j.yebeh.2012.02.007","article-title":"Clinical features of the preictal state: mood changes and premonitory symptoms","volume":"23","author":"haut","year":"2012","journal-title":"Epilepsy & Behavior"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"3379","DOI":"10.1109\/TBME.2012.2215609","article-title":"Automatic segmentation of episodes containing epileptic clonic seizures in video sequences","volume":"59","author":"kalitzin","year":"2012","journal-title":"IEEE Transactions on Biomedical Engineering"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"1960","DOI":"10.1111\/epi.12355","article-title":"Modeling seizure self-prediction: an e-diary study","volume":"54","author":"haut","year":"2013","journal-title":"Epilepsia"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.seizure.2015.01.015"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1111\/epi.13309","article-title":"Heart rate variability in untreated newly diagnosed temporal lobe epilepsy: Evidence for ictal sympathetic dysregulation","volume":"57","author":"romigi","year":"2016","journal-title":"Epilepsia"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/j.seizure.2008.10.007","article-title":"Prodromal symptoms in epileptic patients: clinical characterization of the preictal phase","volume":"18","author":"scaramelli","year":"2009","journal-title":"Seizure"},{"key":"ref1","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1111\/epi.12550","article-title":"ILAE official report: a practical clinical definition of epilepsy","volume":"55","author":"fisher","year":"2014","journal-title":"Epilepsia"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.eplepsyres.2016.05.013","article-title":"Monitoring peri-ictal changes in heart rate variability, oxygen saturation and blood pressure in epilepsy monitoring unit","volume":"125","author":"jaychandran","year":"2016","journal-title":"Epilepsy Research"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2016.01.011"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.eplepsyres.2019.106235"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2010.08.030"}],"event":{"name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","start":{"date-parts":[[2020,10,17]]},"location":"Chengdu, China","end":{"date-parts":[[2020,10,19]]}},"container-title":["2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9263486\/9263487\/09263641.pdf?arnumber=9263641","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T15:40:53Z","timestamp":1656344453000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9263641\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,17]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/cisp-bmei51763.2020.9263641","relation":{},"subject":[],"published":{"date-parts":[[2020,10,17]]}}}