{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T03:08:45Z","timestamp":1772766525499,"version":"3.50.1"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2024,12,27]],"date-time":"2024-12-27T00:00:00Z","timestamp":1735257600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,27]],"date-time":"2024-12-27T00:00:00Z","timestamp":1735257600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1007\/s00521-024-10915-7","type":"journal-article","created":{"date-parts":[[2024,12,27]],"date-time":"2024-12-27T05:28:14Z","timestamp":1735277294000},"page":"4937-4955","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Epileptic signal classification using convolutional neural network and Shapley additive explainable artificial intelligence method"],"prefix":"10.1007","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9176-8124","authenticated-orcid":false,"given":"Prajakta","family":"Rathod","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0785-4282","authenticated-orcid":false,"given":"Shefali","family":"Naik","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6540-6835","authenticated-orcid":false,"given":"Jayendra M.","family":"Bhalodiya","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,27]]},"reference":[{"issue":"4","key":"10915_CR1","doi-asserted-by":"publisher","first-page":"475","DOI":"10.1111\/epi.12550","volume":"55","author":"RS Fisher","year":"2014","unstructured":"Fisher RS et al (2014) ILAE official report: a practical clinical definition of epilepsy. Epilepsia 55(4):475\u2013482","journal-title":"Epilepsia"},{"key":"10915_CR2","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1016\/j.compbiomed.2019.04.031","volume":"109","author":"R San-Segundo","year":"2019","unstructured":"San-Segundo R, Gil-Martin M, D\u2019Haro-Enriquez LF, Pardo JM (2019) Classification of epileptic eeg recordings using signal transforms and convolutional neural networks. Comput Biol Med 109:148\u2013158. https:\/\/doi.org\/10.1016\/j.compbiomed.2019.04.031","journal-title":"Comput Biol Med"},{"key":"10915_CR3","doi-asserted-by":"publisher","first-page":"544","DOI":"10.1016\/j.patrec.2019.10.029","volume":"128","author":"DK Thara","year":"2019","unstructured":"Thara DK, Prema Sudha BG, Xiong F (2019) Auto-detection of epileptic seizure events using deep neural network with different feature scaling techniques. Pattern Recogn Lett 128:544\u2013550. https:\/\/doi.org\/10.1016\/j.patrec.2019.10.029","journal-title":"Pattern Recogn Lett"},{"key":"10915_CR4","doi-asserted-by":"publisher","first-page":"103919","DOI":"10.1016\/j.compbiomed.2020.10391","volume":"124","author":"X Hu","year":"2020","unstructured":"Hu X, Yuan S, Xu F, Leng Y, Yuan K, Yuan Q (2020) Scalp eeg classification using deep bi-lstm network for seizure detection. Comput Biol Med 124:103919. https:\/\/doi.org\/10.1016\/j.compbiomed.2020.10391","journal-title":"Comput Biol Med"},{"key":"10915_CR5","doi-asserted-by":"publisher","first-page":"375","DOI":"10.3389\/fneur.2020.00375","volume":"11","author":"Y Gao","year":"2020","unstructured":"Gao Y, Gao B, Chen Q, Liu J, Zhang Y (2020) Deep convolutional neural network-based epileptic electroencephalogram (eeg) signal classification. Front Neurol 11:375. https:\/\/doi.org\/10.3389\/fneur.2020.00375","journal-title":"Front Neurol"},{"key":"10915_CR6","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1007\/s41666-022-00114-1","volume":"6","author":"CC Yang","year":"2022","unstructured":"Yang CC (2022) Explainable artificial intelligence for predictive modeling in healthcare. J Healthc Inform Res 6:228\u2013239. https:\/\/doi.org\/10.1007\/s41666-022-00114-1","journal-title":"J Healthc Inform Res"},{"key":"10915_CR7","doi-asserted-by":"publisher","unstructured":"Rathod P, Naik S (2022) \u201cReview on epilepsy detection with explainable artificial intelligence,\u201d In: 2022 10th international conference on emerging trends in engineering and technology\u2014signal and information processing (ICETET-SIP-22), pp. 1\u20136, https:\/\/doi.org\/10.1109\/ICETET-SIP-2254415.2022.9791595.","DOI":"10.1109\/ICETET-SIP-2254415.2022.9791595"},{"issue":"10","key":"10915_CR8","doi-asserted-by":"publisher","first-page":"4903","DOI":"10.1109\/JBHI.2022.3159531","volume":"26","author":"A Shankar","year":"2022","unstructured":"Shankar A, Dandapat S, Barma S (2022) Seizure types classification by generating input images with in-depth features from decomposed EEG signals for deep learning pipeline. IEEE J Biomed Health Inform 26(10):4903\u20134912. https:\/\/doi.org\/10.1109\/JBHI.2022.3159531","journal-title":"IEEE J Biomed Health Inform"},{"key":"10915_CR9","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1016\/j.neunet.2020.01.017","volume":"124","author":"S Raghu","year":"2020","unstructured":"Raghu S, Sriraam N, Temel Y, Rao SV, Kubben PL (2020) EEG based multi-class seizure type classification using convolutional neural network and transfer learning. Neural Netw 124:202\u2013212","journal-title":"Neural Netw"},{"key":"10915_CR10","doi-asserted-by":"publisher","first-page":"102322","DOI":"10.1016\/j.bspc.2020.102322","volume":"64","author":"J Prabin Jose","year":"2021","unstructured":"Prabin Jose J, Sundaram M, Jaffino G (2021) Adaptive rag-bull rider: a modified self-adaptive optimization algorithm for epileptic seizure detection with deep stacked autoencoder using electroencephalogram. Biomed Signal Proc Control 64:102322. https:\/\/doi.org\/10.1016\/j.bspc.2020.102322","journal-title":"Biomed Signal Proc Control"},{"issue":"6","key":"10915_CR11","doi-asserted-by":"publisher","first-page":"e07258","DOI":"10.1016\/j.heliyon.2021.e07258","volume":"7","author":"MC Guerrero","year":"2021","unstructured":"Guerrero MC, Parada JS, Espitia HE (2021) EEG signal analysis using classification techniques: Logistic regression, artificial neural networks, support vector machines, and convolutional neural networks. Heliyon 7(6):e07258. https:\/\/doi.org\/10.1016\/j.heliyon.2021.e07258","journal-title":"Heliyon"},{"key":"10915_CR12","doi-asserted-by":"publisher","first-page":"60141","DOI":"10.1109\/ACCESS.2022.3176367","volume":"10","author":"I Jemal","year":"2022","unstructured":"Jemal I, Mezghani N, Abou-Abbas L, Mitiche A (2022) An interpretable deep learning classifier for epileptic seizure prediction using EEG data. IEEE Access 10:60141\u201360150. https:\/\/doi.org\/10.1109\/ACCESS.2022.3176367","journal-title":"IEEE Access"},{"key":"10915_CR13","doi-asserted-by":"publisher","unstructured":"Rathod P, Bhalodiya J, Naik S (2022) \u201cEpilepsy Detection using Bi-LSTM with Explainable Artificial Intelligence,\u201d In: 2022 IEEE 19th India council international conference (INDICON), Kochi, India, pp. 1-6, https:\/\/doi.org\/10.1109\/INDICON56171.2022.10039816","DOI":"10.1109\/INDICON56171.2022.10039816"},{"issue":"6","key":"10915_CR14","doi-asserted-by":"publisher","first-page":"1949","DOI":"10.1109\/JBHI.2020.3037693","volume":"25","author":"N Banluesombatkul","year":"2021","unstructured":"Banluesombatkul N et al (2021) MetaSleepLearner: a pilot study on fast adaptation of bio-signals-based sleep stage classifier to new individual subject using meta-learning. IEEE J Biomed Health Inform 25(6):1949\u20131963. https:\/\/doi.org\/10.1109\/JBHI.2020.3037693","journal-title":"IEEE J Biomed Health Inform"},{"key":"10915_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/AIPR52630.2021.9762082","volume":"2021","author":"M Sidulova","year":"2021","unstructured":"Sidulova M, Nehme N, Park CH (2021) Towards explainable image analysis for Alzheimer\u2019s disease and mild cognitive impairment diagnosis. IEEE Appl Imagery Pattern Recogn Workshop (AIPR) 2021:1\u20136. https:\/\/doi.org\/10.1109\/AIPR52630.2021.9762082","journal-title":"IEEE Appl Imagery Pattern Recogn Workshop (AIPR)"},{"key":"10915_CR16","doi-asserted-by":"publisher","unstructured":"Li G, Adeel Khan M, (2019) \u201cDeep learning on VR-induced attention,\u201d In: 2019 IEEE international conference on artificial intelligence and virtual reality (AIVR), pp. 163\u20131633, https:\/\/doi.org\/10.1109\/AIVR46125.2019.00033.","DOI":"10.1109\/AIVR46125.2019.00033"},{"key":"10915_CR17","unstructured":"Lundberg S, Lee SI. A unified approach to interpreting model predictions. 2017. arXiv:1705.07874."},{"key":"10915_CR18","volume-title":"Beyond Explainable AI Lecture notes in Computer Science","author":"A Holzinger","year":"2022","unstructured":"Holzinger A, Saranti A, Molnar C, Biecek P, Samek W (2022) Explainable AI methods\u2014a brief overview. In: Holzinger A, Goebel R, Fong R, Moon T, Muller KR, Samek W (eds) Beyond Explainable AI Lecture notes in Computer Science. Springer, Cham"},{"key":"10915_CR19","doi-asserted-by":"crossref","unstructured":"Veloso L, McHugh JR, Von Weltin E, Obeid I, Picone J (2017) Big data resources for EEGs: enabling deep learning research. In Obeid I, Picone J (Eds.), In: Proceedings of the IEEE signal processing in medicine and biology symposium (p. 1). Philadelphia, Pennsylvania, USA: IEEE.","DOI":"10.1109\/SPMB.2017.8257044"},{"key":"10915_CR20","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1016\/j.procs.2019.12.112","volume":"163","author":"N Salem","year":"2019","unstructured":"Salem N, Malik H, Shams A (2019) Medical image enhancement based on histogram algorithms. Procedia Comput Sci 163:300\u2013311. https:\/\/doi.org\/10.1016\/j.procs.2019.12.112","journal-title":"Procedia Comput Sci"},{"key":"10915_CR21","doi-asserted-by":"publisher","unstructured":"Islam SM, Mondal HS (2019) \u201cImage enhancement based medical image analysis,\u201d In: 10th international conference on computing, communication and networking technologies (ICCCNT), Kanpur, India, 2019, pp. 1\u20135, https:\/\/doi.org\/10.1109\/ICCCNT45670.2019.8944910.","DOI":"10.1109\/ICCCNT45670.2019.8944910"},{"key":"10915_CR22","unstructured":"Sharpen image using unsharp masking - MATLAB imsharpen\u2014MathWorks India."},{"key":"10915_CR23","unstructured":"Contrast Enhancement Techniques - MATLAB & Simulink\u2014MathWorks India."},{"key":"10915_CR24","unstructured":"Convert RGB to CIE 1976 L*a*b* - MATLAB rgb2lab\u2014MathWorks India."},{"key":"10915_CR25","unstructured":"Enhance contrast using histogram equalization\u2014MATLAB histeq\u2014MathWorks India."},{"key":"10915_CR26","unstructured":"Convert CIE 1976 L*a*b* to RGB\u2014MATLAB lab2rgb\u2014MathWorks India."},{"issue":"11","key":"10915_CR27","doi-asserted-by":"publisher","first-page":"2660","DOI":"10.1109\/TNNLS.2016.2599820","volume":"28","author":"W Samek","year":"2017","unstructured":"Samek W, Binder A, Montavon G, Lapuschkin S, M\u00fcller K-R (2017) Evaluating the visualization of what a deep neural network has learned. IEEE Trans Neural Netw Learn Syst 28(11):2660\u20132673. https:\/\/doi.org\/10.1109\/TNNLS.2016.2599820","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"10915_CR28","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1038\/s41598-019-56958-y","volume":"10","author":"KO Cho","year":"2020","unstructured":"Cho KO, Jang HJ (2020) Comparison of different input modalities and network structures for deep learning-based seizure detection. Sci Rep 10:122. https:\/\/doi.org\/10.1038\/s41598-019-56958-y","journal-title":"Sci Rep"},{"issue":"4","key":"10915_CR29","doi-asserted-by":"publisher","first-page":"1542","DOI":"10.1109\/TCSII.2020.3031399","volume":"68","author":"D Hu","year":"2021","unstructured":"Hu D, Cao J, Lai X, Wang Y, Wang S, Ding Y (2021) Epileptic state classification by fusing hand-crafted and deep learning EEG features. IEEE Trans Circuits Syst II Express Briefs 68(4):1542\u20131546. https:\/\/doi.org\/10.1109\/TCSII.2020.3031399","journal-title":"IEEE Trans Circuits Syst II Express Briefs"},{"key":"10915_CR30","doi-asserted-by":"publisher","first-page":"104076","DOI":"10.1016\/j.bspc.2022.104076","volume":"79","author":"A Einizade","year":"2023","unstructured":"Einizade A, Nasiri S, Mozafari M, Sardouie SH, Clifford GD (2023) Explainable automated seizure detection using attentive deep multi-view networks. Biomed Signal Process Control 79:104076. https:\/\/doi.org\/10.1016\/j.bspc.2022.104076","journal-title":"Biomed Signal Process Control"},{"key":"10915_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/JTEHM.2021.3050925","volume":"9","author":"M Rashed-Al-Mahfuz","year":"2021","unstructured":"Rashed-Al-Mahfuz M, Moni MA, Uddin S, Alyami SA, Summers MA, Eapen V (2021) \u201cA deep convolutional neural network method to detect seizures and characteristic frequencies using epileptic electroencephalogram (EEG) data.\u201d IEEE J Trans Eng Health Med 9:1\u201312. https:\/\/doi.org\/10.1109\/JTEHM.2021.3050925","journal-title":"IEEE J Trans Eng Health Med"},{"issue":"16","key":"10915_CR32","doi-asserted-by":"publisher","first-page":"26126","DOI":"10.1109\/JSEN.2024.3422388","volume":"24","author":"Y Ding","year":"2024","unstructured":"Ding Y, Zhao W (2024) Channel selection for seizure detection based on explainable AI with shapley values. IEEE Sens J 24(16):26126\u201326135. https:\/\/doi.org\/10.1109\/JSEN.2024.3422388","journal-title":"IEEE Sens J"},{"issue":"10","key":"10915_CR33","doi-asserted-by":"publisher","first-page":"5742","DOI":"10.1109\/JBHI.2024.3396130","volume":"28","author":"I Ahmad","year":"2024","unstructured":"Ahmad I et al (2024) Robust epileptic seizure detection based on biomedical signals using an advanced multi-view deep feature learning approach. IEEE J Biomed Health Inform 28(10):5742\u20135754. https:\/\/doi.org\/10.1109\/JBHI.2024.3396130","journal-title":"IEEE J Biomed Health Inform"},{"issue":"6","key":"10915_CR34","doi-asserted-by":"publisher","first-page":"3236","DOI":"10.1109\/JBHI.2024.3366341","volume":"28","author":"I Ahmad","year":"2024","unstructured":"Ahmad I, Zhu M, Li G, Javeed D, Kumar P, Chen S (2024) A secure and interpretable AI for smart healthcare system: a case study on epilepsy diagnosis using EEG signals. IEEE J Biomed Health Inform 28(6):3236\u20133247. https:\/\/doi.org\/10.1109\/JBHI.2024.3366341","journal-title":"IEEE J Biomed Health Inform"},{"issue":"10","key":"10915_CR35","doi-asserted-by":"publisher","first-page":"5428","DOI":"10.1109\/TFUZZ.2024.3434709","volume":"32","author":"FA Khan","year":"2024","unstructured":"Khan FA, Umar Z, Jolfaei A, Tariq M (2024) Explainable fuzzy deep learning for prediction of epileptic seizures using EEG. IEEE Trans Fuzzy Syst 32(10):5428\u20135437. https:\/\/doi.org\/10.1109\/TFUZZ.2024.3434709","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"10915_CR36","doi-asserted-by":"publisher","first-page":"114126","DOI":"10.1016\/j.dss.2023.114126","volume":"178","author":"S Bouazizi","year":"2024","unstructured":"Bouazizi S, Ltifi H (2024) Enhancing accuracy and interpretability in EEG-based medical decision making using an explainable ensemble learning framework application for stroke prediction. Decision Support Syst 178:114126. https:\/\/doi.org\/10.1016\/j.dss.2023.114126","journal-title":"Decision Support Syst"},{"key":"10915_CR37","doi-asserted-by":"publisher","first-page":"106322","DOI":"10.1016\/j.bspc.2024.106322","volume":"95","author":"H Amrani","year":"2024","unstructured":"Amrani H, Adadi A, Berrada M (2024) An explainable hybrid DNN model for seizure versus non-seizure classification and seizure localization using multi-dimensional EEG signals. Biomed Signal Process Control 95:106322. https:\/\/doi.org\/10.1016\/j.bspc.2024.106322","journal-title":"Biomed Signal Process Control"},{"key":"10915_CR38","doi-asserted-by":"publisher","first-page":"123991","DOI":"10.1016\/j.eswa.2024.123991","volume":"251","author":"S Abhishek","year":"2024","unstructured":"Abhishek S, Sachin KS, Mohan N, Soman KP (2024) EEG based automated detection of seizure using machine learning approach and traditional features. Expert Syst Appl 251:123991. https:\/\/doi.org\/10.1016\/j.eswa.2024.123991","journal-title":"Expert Syst Appl"},{"key":"10915_CR39","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1016\/j.seizure.2024.03.013","volume":"118","author":"X Ye","year":"2024","unstructured":"Ye X, Panpan H, Yang B, Yang Y, Gao D, Zeng GQ, Wang K (2024) Using scalp EEG to predict seizure recurrence and electrical status epilepticus in children with idiopathic focal epilepsy. Seizure European J Epilepsy 118:8\u201316. https:\/\/doi.org\/10.1016\/j.seizure.2024.03.013","journal-title":"Seizure European J Epilepsy"},{"key":"10915_CR40","doi-asserted-by":"publisher","first-page":"103654","DOI":"10.1016\/j.jisa.2023.103654","volume":"80","author":"I Ahmad","year":"2024","unstructured":"Ahmad I, Yao C, Li L, Chen Y, Liu Z, Ullah I, Shabaz M, Wang X, Huang K, Li G, Zhao G, Samuel OW, Chen S (2024) An efficient feature selection and explainable classification method for EEG-based epileptic seizure detection. J Inform Secur Appl 80:103654. https:\/\/doi.org\/10.1016\/j.jisa.2023.103654","journal-title":"J Inform Secur Appl"},{"key":"10915_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcan.2024.08.013","author":"FA Khan","year":"2024","unstructured":"Khan FA, Umar Z, Jolfaei A, Tariq M (2024) Explainable AI for epileptic seizure detection in internet of medical things. Digital Commun Netw. https:\/\/doi.org\/10.1016\/j.dcan.2024.08.013","journal-title":"Digital Commun Netw"},{"key":"10915_CR42","doi-asserted-by":"publisher","unstructured":"Chapatwala N, Paunwala CN, Dalal P, (2022) \u201cAn explainable AI approach towards epileptic seizure detection,\u201d In: 2022 IEEE 19th India council international conference (INDICON), Kochi, India, pp. 1-6, https:\/\/doi.org\/10.1109\/INDICON56171.2022.10039982","DOI":"10.1109\/INDICON56171.2022.10039982"},{"key":"10915_CR43","doi-asserted-by":"publisher","unstructured":"Gupta GRNP, Guha D, Mahadevappa M, Chakraborty D, (2023) \u201cOrdered weighted aggregation operators based statistical features for seizure classification using EEG,\u201d In: IEEE 20th India council international conference (INDICON), Hyderabad, India, pp. 293-298, https:\/\/doi.org\/10.1109\/INDICON59947.2023.10440939","DOI":"10.1109\/INDICON59947.2023.10440939"},{"key":"10915_CR44","doi-asserted-by":"publisher","unstructured":"K. Sudhamayee, M. Gopal Krishna, P. Manimaran, Simplicial network analysis on EEG signals, Physica A: Statistical Mechanics and its Applications, Volume 630, 2023, 129230, ISSN 0378\u20134371, https:\/\/doi.org\/10.1016\/j.physa.2023.129230. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0378437123007859)","DOI":"10.1016\/j.physa.2023.129230"},{"key":"10915_CR45","doi-asserted-by":"publisher","first-page":"106763","DOI":"10.1016\/j.engappai.2023.106763","volume":"125","author":"I Huang","year":"2023","unstructured":"Huang I, Duan J (2023) GFBLS: graph-regularized fuzzy broad learning system for detection of interictal epileptic discharges. Eng Appl Artificial Intel 125:106763. https:\/\/doi.org\/10.1016\/j.engappai.2023.106763","journal-title":"Eng Appl Artificial Intel"},{"key":"10915_CR46","doi-asserted-by":"publisher","first-page":"122424","DOI":"10.1016\/j.eswa.2023.122424","volume":"239","author":"RN Gowtham","year":"2024","unstructured":"Gowtham RN, Hait SR, Guha D, Mahadevappa M (2024) Classification of epileptic EEG signals with the utilization of Bonferroni mean based fuzzy pattern tree. Expert Syst Appl 239:122424. https:\/\/doi.org\/10.1016\/j.eswa.2023.122424","journal-title":"Expert Syst Appl"},{"key":"10915_CR47","doi-asserted-by":"publisher","first-page":"103349","DOI":"10.1016\/j.dsp.2021.103349","volume":"122","author":"G Jaffino","year":"2022","unstructured":"Jaffino G, Sundaram M, Prabin Jose J (2022) Weighted 1D-local binary pattern features and Taylor\u2013Henry gas solubility optimization based deep maxout network for discovering epileptic seizure using EEG. Digital Signal Process 122:103349. https:\/\/doi.org\/10.1016\/j.dsp.2021.103349","journal-title":"Digital Signal Process"},{"key":"10915_CR48","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TIM.2022.3217515","volume":"71","author":"MNA Tawhid","year":"2022","unstructured":"Tawhid MNA, Siuly S, Li T (2022) A convolutional long short-term memory-based neural network for epilepsy detection from EEG. IEEE Trans Instrument Measure 71:1\u201311. https:\/\/doi.org\/10.1109\/TIM.2022.3217515","journal-title":"IEEE Trans Instrument Measure"},{"issue":"9","key":"10915_CR49","doi-asserted-by":"publisher","DOI":"10.1002\/eng2.12827","volume":"6","author":"SM Omar","year":"2024","unstructured":"Omar SM, Kimwele M, Olowolayemo A, Kaburu DM (2024) Enhancing EEG signals classification using LSTM-CNN architecture. Eng Reports 6(9):e12827. https:\/\/doi.org\/10.1002\/eng2.12827","journal-title":"Eng Reports"},{"key":"10915_CR50","doi-asserted-by":"publisher","first-page":"304","DOI":"10.1109\/TNSRE.2024.3350074","volume":"32","author":"Y Tang","year":"2024","unstructured":"Tang Y, Wu Q, Mao H, Guo L (2024) Epileptic seizure detection based on path signature and Bi-LSTM network with attention mechanism. IEEE Trans Neural Syst Rehabil Eng 32:304\u2013313. https:\/\/doi.org\/10.1109\/TNSRE.2024.3350074","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"key":"10915_CR51","doi-asserted-by":"publisher","first-page":"20605","DOI":"10.1007\/s00521-023-08832-2","volume":"35","author":"S Shanmugam","year":"2023","unstructured":"Shanmugam S, Dharmar S (2023) A CNN-LSTM hybrid network for automatic seizure detection in EEG signals. Neural Comput Applic 35:20605\u201320617. https:\/\/doi.org\/10.1007\/s00521-023-08832-2","journal-title":"Neural Comput Applic"},{"key":"10915_CR52","doi-asserted-by":"publisher","first-page":"12195","DOI":"10.1007\/s00521-023-08350-1","volume":"35","author":"DL de Vargas","year":"2023","unstructured":"de Vargas DL, Oliva JT, Teixeira M et al (2023) Feature extraction and selection from electroencephalogram signals for epileptic seizure diagnosis. Neural Comput Applic 35:12195\u201312219. https:\/\/doi.org\/10.1007\/s00521-023-08350-1","journal-title":"Neural Comput Applic"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10915-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-024-10915-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10915-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,8]],"date-time":"2025-02-08T19:34:09Z","timestamp":1739043249000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-024-10915-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,27]]},"references-count":52,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025,2]]}},"alternative-id":["10915"],"URL":"https:\/\/doi.org\/10.1007\/s00521-024-10915-7","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,27]]},"assertion":[{"value":"18 April 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 December 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 December 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no competing interest to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"We obtained the necessary approvals to conduct a study on an anonymized and publicly available dataset from the biomedical research ethics committee at the university.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"The study proposed a method for epilepsy diagnosis validated with an open-access dataset. It does not claim or report a clinical trial.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Clinical trial"}}]}}