Cross-patient seizure prediction via continuous domain adaptation and similar sample replay

Al-gumaei AH, Azam M, Amayri M, Bouguila N (2023) Ica and iva bounded multivariate generalized gaussian mixture based hidden markov models. Eng Appl Artif Intell 123:106345

Article  Google Scholar 

Atal DK, Singh M (2023) Effectual seizure detection using mbbf-gpso with cnn network. Cognit Neurodyn 18(3):907–918

Article  Google Scholar 

Bhattacharya A, Baweja T, Karri S (2022) Epileptic seizure prediction using deep transformer model. Int J Neural Syst 32(02):2150058

Article  PubMed  Google Scholar 

Cook MJ, O’Brien TJ, Berkovic SF, Murphy M, Morokoff A, Fabinyi G, D’Souza W, Yerra R, Archer J, Litewka L (2013) Prediction of seizure likelihood with a long-term, implanted seizure advisory system in patients with drug-resistant epilepsy: a first-in-man study. Lancet Neurol 12(6):563–571

Article  PubMed  Google Scholar 

Deng Z, Li C, Song R, Liu X, Qian R, Chen X (2023) Eeg-based seizure prediction via hybrid vision transformer and data uncertainty learning. Eng Appl Artif Intell 123:106401

Article  Google Scholar 

Gao Q, Omran AH, Baghersad Y, Mohammadi O, Alkhafaji MA, Al-Azzawi AKJ, Al-Khafaji SH, Emami N, Toghraie D, Golkar MJ (2023) Electroencephalogram signal classification based on fourier transform and pattern recognition network for epilepsy diagnosis. Eng Appl Artif Intell 123:106479

Article  Google Scholar 

Goldberger AL, Amaral LA, Glass L, Hausdorff JM, Ivanov PC, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE (2000) Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals. Circulation 101(23):215–220

Article  Google Scholar 

He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 770–778

Islam MR, Zhao X, Miao Y, Sugano H, Tanaka T (2023) Epileptic seizure focus detection from interictal electroencephalogram: a survey. Cognit Neurodyn 17(1):1–23

Article  Google Scholar 

Khan H, Marcuse L, Fields M, Swann K, Yener B (2017) Focal onset seizure prediction using convolutional networks. IEEE Trans Biomed Eng 65(9):2109–2118

Article  PubMed  Google Scholar 

Kuhlmann L, Karoly P, Freestone DR, Brinkmann BH, Temko A, Barachant A, Li F, Titericz G Jr, Lang BW, Lavery D (2018) Epilepsyecosystem. org: crowd-sourcing reproducible seizure prediction with long-term human intracranial eeg. Brain 141(9):2619–2630

PubMed  PubMed Central  Google Scholar 

Liang D, Liu A, Wu L, Li C, Qian R, Ward RK, Chen X (2022) Semisupervised seizure prediction in scalp eeg using consistency regularization. J Healthcare Eng. https://doi.org/10.1155/2022/1573076

Article  Google Scholar 

Maimaiti B, Meng H, Lv Y, Qiu J, Zhu Z, Xie Y, Li Y, Zhao W, Liu J, Li M (2022) An overview of eeg-based machine learning methods in seizure prediction and opportunities for neurologists in this field. Neuroscience 481:197–218

Article  CAS  PubMed  Google Scholar 

Maiwald T, Winterhalder M, Aschenbrenner-Scheibe R, Voss HU, Schulze-Bonhage A, Timmer J (2004) Comparison of three nonlinear seizure prediction methods by means of the seizure prediction characteristic. Physica D: Nonlinear Phenom 194(3–4):357–368

Article  Google Scholar 

Pan Y, Yao T, Li Y, Wang Y, Ngo C-W, Mei T (2019) Transferrable prototypical networks for unsupervised domain adaptation. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp. 2239–2247

Peng P, Song Y, Yang L (2021) Seizure prediction in eeg signals using stft and domain adaptation. Front Neurosci 15:825434

Article  PubMed  Google Scholar 

Peng P, Xie L, Zhang K, Zhang J, Yang L, Wei H (2022) Domain adaptation for epileptic eeg classification using adversarial learning and riemannian manifold. Biomed Signal Process Control 75:103555

Article  Google Scholar 

Peng X, Bai Q, Xia X, Huang Z, Saenko K, Wang B (2019) Moment matching for multi-source domain adaptation. In: Proceedings of the IEEE/CVF international conference on computer vision, pp. 1406–1415

Pinto MF, Leal A, Lopes F, Pais J, Dourado A, Sales F, Martins P, Teixeira CA (2022) On the clinical acceptance of black-box systems for eeg seizure prediction. Epilepsia Open 7(2):247–259

Article  PubMed  PubMed Central  Google Scholar 

Rasheed K, Qayyum A, Qadir J, Sivathamboo S, Kwan P, Kuhlmann L, O’Brien T, Razi A (2020) Machine learning for predicting epileptic seizures using eeg signals: A review. IEEE Rev Biomed Eng 14:139–155

Article  Google Scholar 

Sarvi Zargar B, Karami Mollaei MR, Ebrahimi F, Rasekhi J (2023) Generalizable epileptic seizures prediction based on deep transfer learning. Cognit Neurodyn 17(1):119–131

Article  Google Scholar 

Shanmugam S, Dharmar S (2024) Implementation of a non-linear svm classification for seizure eeg signal analysis on fpga. Eng Appl Artif Intell 131:107826

Article  Google Scholar 

Shoeb AH (2009) Application of machine learning to epileptic seizure onset detection and treatment. PhD thesis, Massachusetts institute of technology

Shorvon SD, Andermann F, Guerrini R (2011) The causes of epilepsy: common and uncommon causes in adults and children. Cambridge University Press, England

Book  Google Scholar 

Stirling RE, Cook MJ, Grayden DB, Karoly PJ (2021) Seizure forecasting and cyclic control of seizures. Epilepsia 62:2–14

Article  Google Scholar 

Tang H, Chen K, Jia K (2020) Unsupervised domain adaptation via structurally regularized deep clustering. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp. 8725–8735

Truong ND, Nguyen AD, Kuhlmann L, Bonyadi MR, Yang J, Ippolito S, Kavehei O (2018) Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram. Neural Netw 105:104–111

Article  PubMed  Google Scholar 

Volpi R, Larlus D, Rogez G (2021) Continual adaptation of visual representations via domain randomization and meta-learning. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp. 4443–4453

Wang H, He H, Katabi D (2020) Continuously indexed domain adaptation. In: International conference on machine learning, pp. 9898–9907. PMLR

Yan J, Li J, Xu H, Yu Y, Xu T (2022) Seizure prediction based on transformer using scalp electroencephalogram. Appl Sci 12(9):4158

Article  CAS  Google Scholar 

Yang J, Yan R, Hauptmann AG (2007) Cross-domain video concept detection using adaptive svms. In: Proceedings of the 15th ACM international conference on multimedia, pp. 188–197

Zhang Z, Liu A, Gao Y, Cui X, Qian R, Chen X (2023) Distilling invariant representations with domain adversarial learning for cross-subject children seizure prediction. IEEE transactions on cognitive and developmental systems

Zhang C, Cheng Y, Wei P, He H, Chen J (2022) Cenet: Consolidation-and-exploration network for continuous domain adaptation. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp. 3426–3432

Zhao X, Zhao Q, Tanaka T, Solé-Casals J, Zhou G, Mitsuhashi T, Sugano H, Yoshida N, Cao J (2023) Classification of the epileptic seizure onset zone based on partial annotation. Cognit Neurodyn 17(3):703–713

Article  Google Scholar 

Zhu Y, Zhuang F, Wang J, Ke G, Chen J, Bian J, Xiong H, He Q (2020) Deep subdomain adaptation network for image classification. IEEE Trans Neural Netw Learn Syst 32(4):1713–1722

Article  Google Scholar 

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