{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T07:06:05Z","timestamp":1763535965837,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":25,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,9,24]],"date-time":"2021-09-24T00:00:00Z","timestamp":1632441600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,9,24]]},"DOI":"10.1145\/3488933.3489016","type":"proceedings-article","created":{"date-parts":[[2022,2,25]],"date-time":"2022-02-25T11:36:59Z","timestamp":1645789019000},"page":"419-423","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Epileptic Seizure Prediction by Synthesizing EEG Signals through GPT"],"prefix":"10.1145","author":[{"given":"Rui","family":"Niu","sequence":"first","affiliation":[{"name":"Xi'an University of Posts and Telecommunications, China"}]},{"given":"Yagang","family":"Wang","sequence":"additional","affiliation":[{"name":"Xi'an University of Posts and Telecommunications, China"}]},{"given":"Haole","family":"Xi","sequence":"additional","affiliation":[{"name":"Xi'an University of Posts and Telecommunications, China"}]},{"given":"Yulong","family":"Hao","sequence":"additional","affiliation":[{"name":"Xi'an University of Posts and Telecommunications, China"}]},{"given":"Mei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Lanzhou Jiaotong UniversityLanzhou Jiaotong University, China"}]}],"member":"320","published-online":{"date-parts":[[2022,2,25]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2014.2387795"},{"volume-title":"Neurological Disorders: Public Health Challenges","author":"2006.World Health Organization","key":"e_1_3_2_1_2_1","unstructured":"2006.World Health Organization , Neurological Disorders: Public Health Challenges . Geneva, Switzerland : World Health Organization . 2006.World Health Organization, Neurological Disorders: Public Health Challenges. Geneva, Switzerland: World Health Organization."},{"key":"e_1_3_2_1_3_1","volume-title":"Neurocomputing","volume":"404","author":"Weitong Sun","year":"2020","unstructured":"Weitong Sun , Yuping Su, Xia Wu , Xiaojun Wu , 2020 . \" A novel end-to-end 1D-ResCNN model to remove artifact from EEG signals \", Neurocomputing , Volume 404 , https:\/\/doi.org\/ 10.1016\/j.neucom.2020.04.029. 10.1016\/j.neucom.2020.04.029 Weitong Sun, Yuping Su, Xia Wu, Xiaojun Wu, 2020. \"A novel end-to-end 1D-ResCNN model to remove artifact from EEG signals\", Neurocomputing, Volume 404, https:\/\/doi.org\/ 10.1016\/j.neucom.2020.04.029."},{"key":"e_1_3_2_1_4_1","first-page":"7569","volume-title":"Annu. Int. Conf. IEEE Eng. Med. Biol. Soc.","author":"Chiang N.-F.","year":"2011","unstructured":"C.-Y . Chiang , N.-F. Chang , T.-C. Chen , H.-H. Chen , and L.-G. Chen , 2011 . \" Seizure prediction based on classification of EEG synchronization patterns with on-line retraining and post-processing scheme,\" in Proc . Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. , Boston, MA, USA , pp. 7564\u2013 7569 . https:\/\/doi.org\/10.1109\/iembs.2011.6091865. 10.1109\/iembs.2011.6091865 C.-Y . Chiang, N.-F. Chang, T.-C. Chen, H.-H. Chen, and L.-G. Chen, 2011. \"Seizure prediction based on classification of EEG synchronization patterns with on-line retraining and post-processing scheme,\" in Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., Boston, MA, USA, pp. 7564\u20137569. https:\/\/doi.org\/10.1109\/iembs.2011.6091865."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBCAS.2019.2929053"},{"key":"e_1_3_2_1_6_1","unstructured":"Journal of Engineering. 2020 Central Nervous System Diseases and Conditions - Epilepsy; Investigators from Centre for Medical Electronics and Computing Zero in on Epilepsy (Automated Detection of Epileptic Seizures Using Successive Decomposition Index and Support Vector Machine Classifier In Long-term Eeg)"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBCAS.2015.2477264"},{"issue":"1","key":"e_1_3_2_1_8_1","article-title":"Epileptic seizure prediction by exploiting spatiotemporal relationship of eeg signals using phase correlation","volume":"24","author":"Parvez MZ","year":"2016","unstructured":"Parvez MZ , Paul M , 2016 . \" Epileptic seizure prediction by exploiting spatiotemporal relationship of eeg signals using phase correlation \". IEEE Trans Neural Syst Rehabilit Eng Publicat IEEE Eng Med Biol Soc 24 ( 1 ):158, https:\/\/doi.org\/10.1109\/tnsre.2015.2458982. 10.1109\/tnsre.2015.2458982 Parvez MZ, Paul M ,2016. \"Epileptic seizure prediction by exploiting spatiotemporal relationship of eeg signals using phase correlation\". IEEE Trans Neural Syst Rehabilit Eng Publicat IEEE Eng Med Biol Soc 24(1):158, https:\/\/doi.org\/10.1109\/tnsre.2015.2458982.","journal-title":"IEEE Trans Neural Syst Rehabilit Eng Publicat IEEE Eng Med Biol Soc"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2016.04.014"},{"key":"#cr-split#-e_1_3_2_1_10_1.1","doi-asserted-by":"crossref","unstructured":"Truong ND Nguyen AD Kuhlmann L Bonyadi MR Yang J Kavehei O 2017. \"A generalized seizure prediction with convolutional neural networks for intracranial and scalp electroencephalogram data analysis\". CoRR abs\/1707.01976 https:\/\/doi.org\/10.1016\/j.neunet.2018.04.018. 10.1016\/j.neunet.2018.04.018","DOI":"10.1016\/j.neunet.2018.04.018"},{"key":"#cr-split#-e_1_3_2_1_10_1.2","doi-asserted-by":"crossref","unstructured":"Truong ND Nguyen AD Kuhlmann L Bonyadi MR Yang J Kavehei O 2017. \"A generalized seizure prediction with convolutional neural networks for intracranial and scalp electroencephalogram data analysis\". CoRR abs\/1707.01976 https:\/\/doi.org\/10.1016\/j.neunet.2018.04.018.","DOI":"10.1016\/j.neunet.2018.04.018"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2018.05.019"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1528-1167.2011.03138.x"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2017.2785401"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2020.3035836"},{"key":"e_1_3_2_1_15_1","first-page":"20080","volume-title":"A Unified Framework and Method for EEG-Based Early Epileptic Seizure Detection and Epilepsy Diagnosis,\" in IEEE Access","author":"Chen G.","year":"2020","unstructured":"Z. Chen , G. Lu , Z. Xie and W. Shang , \" A Unified Framework and Method for EEG-Based Early Epileptic Seizure Detection and Epilepsy Diagnosis,\" in IEEE Access , vol. 8 , pp. 20080 - 20092 , 2020 , https:\/\/doi.org\/10.1109\/ACCESS.2020.2969055. 10.1109\/ACCESS.2020.2969055 Z. Chen, G. Lu, Z. Xie and W. Shang, \"A Unified Framework and Method for EEG-Based Early Epileptic Seizure Detection and Epilepsy Diagnosis,\" in IEEE Access, vol. 8, pp. 20080-20092, 2020, https:\/\/doi.org\/10.1109\/ACCESS.2020.2969055."},{"key":"e_1_3_2_1_16_1","volume-title":"Massachusetts Inst. Technol","author":"Shoeb","year":"2021","unstructured":"A. H. Shoeb , 2009. \"Application of machine learning to epileptic seizure onset detection and treatment,\" Ph . D. dissertation , Massachusetts Inst. Technol . Cambridge, MA , USA. https:\/\/doi.org\/10.1109\/NER49283. 2021 .9441348. 10.1109\/NER49283.2021.9441348 A. H. Shoeb, 2009. \"Application of machine learning to epileptic seizure onset detection and treatment,\" Ph.D. dissertation, Massachusetts Inst. Technol. Cambridge, MA, USA. https:\/\/doi.org\/10.1109\/NER49283.2021.9441348."},{"key":"e_1_3_2_1_17_1","article-title":"A lightweight solution to epileptic seizure prediction based on EEG synchronization measurement","author":"Shasha Zhang","year":"2020","unstructured":"Shasha Zhang , 2020 . \" A lightweight solution to epileptic seizure prediction based on EEG synchronization measurement .\" The Journal of Supercomputing .prepublish. https:\/\/doi.org\/10.1007\/s11227-020-03426-4. 10.1007\/s11227-020-03426-4 Shasha Zhang, 2020. \"A lightweight solution to epileptic seizure prediction based on EEG synchronization measurement.\" The Journal of Supercomputing .prepublish. https:\/\/doi.org\/10.1007\/s11227-020-03426-4.","journal-title":"The Journal of Supercomputing .prepublish. https:\/\/doi.org\/10.1007\/s11227-020-03426-4."},{"key":"#cr-split#-e_1_3_2_1_18_1.1","doi-asserted-by":"crossref","unstructured":"Gao Yunyuan 2020. \"Deep Convolutional Neural Network-Based Epileptic Electroencephalogram (EEG) Signal Classification..\" Frontiers in neurology 11. https:\/\/doi.org\/10.3389\/fneur.2020.00375. 10.3389\/fneur.2020.00375","DOI":"10.3389\/fneur.2020.00375"},{"key":"#cr-split#-e_1_3_2_1_18_1.2","doi-asserted-by":"crossref","unstructured":"Gao Yunyuan 2020. \"Deep Convolutional Neural Network-Based Epileptic Electroencephalogram (EEG) Signal Classification..\" Frontiers in neurology 11. https:\/\/doi.org\/10.3389\/fneur.2020.00375.","DOI":"10.3389\/fneur.2020.00375"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"crossref","unstructured":"Turky N. Alotaiby 2017. \"Epileptic Seizure Prediction Using CSP and LDA for Scalp EEG Signals.\" Computational Intelligence and Neuroscience. https:\/\/doi.org\/10.1155\/2017\/1240323.    10.1155\/2017\nTurky N. Alotaiby 2017. \"Epileptic Seizure Prediction Using CSP and LDA for Scalp EEG Signals.\" Computational Intelligence and Neuroscience. https:\/\/doi.org\/10.1155\/2017\/1240323.","DOI":"10.1155\/2017\/1240323"},{"key":"#cr-split#-e_1_3_2_1_20_1.1","doi-asserted-by":"crossref","unstructured":"J. J. Bird M. Pritchard A. Fratini A. Ek\u00e1rt and D. R. Faria 2021. \"Synthetic Biological Signals Machine-Generated by GPT-2 Improve the Classification of EEG and EMG Through Data Augmentation \" in\u00a0 IEEE Robotics and Automation Letters vol. 6 no. 2 pp. 3498-3504. https:\/\/doi.org\/ 10.1109\/LRA.2021.3056355. 10.1109\/LRA.2021.3056355","DOI":"10.1109\/LRA.2021.3056355"},{"key":"#cr-split#-e_1_3_2_1_20_1.2","doi-asserted-by":"crossref","unstructured":"J. J. Bird M. Pritchard A. Fratini A. Ek\u00e1rt and D. R. Faria 2021. \"Synthetic Biological Signals Machine-Generated by GPT-2 Improve the Classification of EEG and EMG Through Data Augmentation \" in\u00a0 IEEE Robotics and Automation Letters vol. 6 no. 2 pp. 3498-3504. https:\/\/doi.org\/ 10.1109\/LRA.2021.3056355.","DOI":"10.1109\/LRA.2021.3056355"},{"key":"e_1_3_2_1_21_1","first-page":"5998","article-title":"Attention is all you need","year":"2017","unstructured":"A. V aswani 2017 . \" Attention is all you need ,\" in Proc. Adv. Neural Inf.Process. Syst. pp. 5998 \u2013 6008 . A. V aswani 2017. \"Attention is all you need,\" in Proc. Adv. Neural Inf.Process. Syst. pp. 5998\u20136008.","journal-title":"Proc. Adv. Neural Inf.Process. Syst."},{"key":"e_1_3_2_1_22_1","volume-title":"IEEE Engineering in Medicine and Biology Society. Annual Conference. https:\/\/doi.org\/10","author":"Shoeb Ali","year":"2004","unstructured":"Shoeb Ali , 2004 . \" Patient-specific seizure onset detection.\" Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society . IEEE Engineering in Medicine and Biology Society. Annual Conference. https:\/\/doi.org\/10 .1016\/j.yebeh.2004.05.005. 10.1016\/j.yebeh.2004.05.005 Shoeb Ali, 2004. \"Patient-specific seizure onset detection.\" Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference. https:\/\/doi.org\/10.1016\/j.yebeh.2004.05.005."}],"event":{"name":"AIPR 2021: 2021 4th International Conference on Artificial Intelligence and Pattern Recognition","acronym":"AIPR 2021","location":"Xiamen China"},"container-title":["2021 4th International Conference on Artificial Intelligence and Pattern Recognition"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3488933.3489016","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3488933.3489016","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:49:00Z","timestamp":1750193340000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3488933.3489016"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,24]]},"references-count":25,"alternative-id":["10.1145\/3488933.3489016","10.1145\/3488933"],"URL":"https:\/\/doi.org\/10.1145\/3488933.3489016","relation":{},"subject":[],"published":{"date-parts":[[2021,9,24]]},"assertion":[{"value":"2022-02-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}