Fisher, R. S. et al. ILAE official report: A practical clinical definition of epilepsy. Epilepsia 55, 475482 (2014).

Article PubMed Google Scholar

Tatum, W. O. et al. Clinical utility of EEG in diagnosing and monitoring epilepsy in adults. Clin. Neurophysiol. 129, 10561082 (2018).

Article CAS PubMed Google Scholar

Pillai, J. & Sperling, M. R. Interictal EEG and the diagnosis of epilepsy. Epilepsia 47, 1422 (2006).

Article PubMed Google Scholar

Baldin, E., Hauser, W. A., Buchhalter, J. R., Hesdorffer, D. C. & Ottman, R. Yield of epileptiform electroencephalogram abnormalities in incident unprovoked seizures: A population-based study. Epilepsia 55, 13891398 (2014).

Article PubMed PubMed Central Google Scholar

Bouma, H. K., Labos, C., Gore, G. C., Wolfson, C. & Keezer, M. R. The diagnostic accuracy of routine electroencephalography after a first unprovoked seizure. Eur. J. Neurol. 23, 455463 (2016).

Article CAS PubMed Google Scholar

Jing, J. et al. Interrater reliability of experts in identifying interictal epileptiform discharges in electroencephalograms. JAMA Neurol. 77, 4957 (2020).

Article PubMed Google Scholar

Amin, U. & Benbadis, S. R. The role of EEG in the erroneous diagnosis of epilepsy. J. Clin. Neurophysiol. 36, 294297 (2019).

Article PubMed Google Scholar

Chadwick, D. & Smith, D. The misdiagnosis of epilepsy. BMJ 324, 495496 (2002).

Article PubMed PubMed Central Google Scholar

Seneviratne, U., Cook, M. & DSouza, W. The electroencephalogram of idiopathic generalized epilepsy. Epilepsia 53, 234248 (2012).

Article PubMed Google Scholar

Seneviratne, U., Boston, R. C., Cook, M. & DSouza, W. EEG correlates of seizure freedom in genetic generalized epilepsies. Neurol. Clin. Pract. 7, 3544 (2017).

Article PubMed PubMed Central Google Scholar

Guida, M., Iudice, A., Bonanni, E. & Giorgi, F. S. Effects of antiepileptic drugs on interictal epileptiform discharges in focal epilepsies: An update on current evidence. Expert Rev. Neurother. 15, 947959 (2015).

Article CAS PubMed Google Scholar

Arntsen, V., Sand, T., Syvertsen, M. R. & Brodtkorb, E. Prolonged epileptiform EEG runs are associated with persistent seizures in juvenile myoclonic epilepsy. Epilepsy Res. 134, 2632 (2017).

Article PubMed Google Scholar

Acharya, U. R., Vinitha Sree, S., Swapna, G., Martis, R. J. & Suri, J. S. Automated EEG analysis of epilepsy: A review. Knowl.-Based Syst. 45, 147165 (2013).

Article Google Scholar

Woldman, W. et al. Dynamic network properties of the interictal brain determine whether seizures appear focal or generalised. Sci. Rep. 10, 7043 (2020).

Article ADS CAS PubMed PubMed Central Google Scholar

Chowdhury, F. A. et al. Revealing a brain network endophenotype in families with idiopathic generalised epilepsy. PLoS ONE 9, e110136 (2014).

Article ADS PubMed PubMed Central Google Scholar

Varatharajah, Y. et al. Quantitative analysis of visually reviewed normal scalp EEG predicts seizure freedom following anterior temporal lobectomy. Epilepsia 63, 16301642 (2022).

Article PubMed PubMed Central Google Scholar

Abela, E. et al. Slower alpha rhythm associates with poorer seizure control in epilepsy. Ann. Clin. Transl. Neurol. 6(2), 333343 (2019).

Article PubMed Google Scholar

Larsson, P. G. & Kostov, H. Lower frequency variability in the alpha activity in EEG among patients with epilepsy. Clin. Neurophysiol. 116, 27012706 (2005).

Article PubMed Google Scholar

Pegg, E. J., Taylor, J. R. & Mohanraj, R. Spectral power of interictal EEG in the diagnosis and prognosis of idiopathic generalized epilepsies. Epilepsy Behav. 112, 107427 (2020).

Article PubMed Google Scholar

Larsson, P. G., Eeg-Olofsson, O. & Lantz, G. Alpha frequency estimation in patients with epilepsy. Clin. EEG Neurosci. 43(2), 97104 (2012).

Article PubMed Google Scholar

Miyauchi, T., Endo, K., Yamaguchi, T. & Hagimoto, H. Computerized analysis of EEG background activity in epileptic patients. Epilepsia 32, 870881 (1991).

Article CAS PubMed Google Scholar

Diaz, G. F. et al. Generalized background qEEG abnormalities in localized symptomatic epilepsy. Electroencephalogr. Clin. Neurophysiol. 106(6), 501507 (1998).

Article CAS PubMed Google Scholar

Urigen, J. A., Garca-Zapirain, B., Artieda, J., Iriarte, J. & Valencia, M. Comparison of background EEG activity of different groups of patients with idiopathic epilepsy using Shannon spectral entropy and cluster-based permutation statistical testing. PLoS ONE 12, e0184044 (2017).

Article PubMed PubMed Central Google Scholar

Sathyanarayana, A. et al. Measuring the effects of sleep on epileptogenicity with multifrequency entropy. Clin. Neurophysiol. 132, 20122018 (2021).

Article PubMed PubMed Central Google Scholar

Luo, K. & Luo, D. An EEG feature-based diagnosis model for epilepsy. in 2010 International Conference on Computer Application and System Modeling (ICCASM 2010) vol. 8 V8592-V8594 (2010).

Faiman, I., Smith, S., Hodsoll, J., Young, A. H. & Shotbolt, P. Resting-state EEG for the diagnosis of idiopathic epilepsy and psychogenic nonepileptic seizures: A systematic review. Epilepsy Behav. 121, 108047 (2021).

Article PubMed Google Scholar

Engel, J. Jr., Bragin, A. & Staba, R. Nonictal EEG biomarkers for diagnosis and treatment. Epilepsia Open 3, 120126 (2018).

Article PubMed PubMed Central Google Scholar

Dash, D. et al. Update on minimal standards for electroencephalography in Canada: A review by the Canadian Society of Clinical Neurophysiologists. Can. J. Neurol. Sci./J. Can. des Sci. Neurologiques 44, 631642 (2017).

Article Google Scholar

Jas, M., Engemann, D. A., Bekhti, Y., Raimondo, F. & Gramfort, A. Autoreject: Automated artifact rejection for MEG and EEG data. Neuroimage 159, 417429 (2017).

Article PubMed Google Scholar

Gandhi, T., Panigrahi, B. K. & Anand, S. A comparative study of wavelet families for EEG signal classification. Neurocomputing 74, 30513057 (2011).

Article Google Scholar

Zou, H. & Hastie, T. Regularization and variable selection via the elastic net. J. R. Stat. Soc. Ser. B 67, 301320 (2005).

Article MathSciNet MATH Google Scholar

Ke, G. et al. LightGBM: A highly efficient gradient boosting decision tree. In Proceedings of the 31st International Conference on Neural Information Processing Systems (ed. Ke, G.) 31493157 (Curran Associates Inc, 2017).

Google Scholar

Cawley, G. C. & Talbot, N. L. C. On over-fitting in model selection and subsequent selection bias in performance evaluation. J. Mach. Learn. Res. 11, 20792107 (2010).

MathSciNet MATH Google Scholar

LeDell, E., Petersen, M. & van der Laan, M. Computationally efficient confidence intervals for cross-validated area under the ROC curve estimates. Electron. J. Stat. 9, 15831607 (2015).

Article MathSciNet PubMed PubMed Central MATH Google Scholar

DeLong, E. R., DeLong, D. M. & Clarke-Pearson, D. L. Comparing the areas under two or more correlated receiver operating characteristic curves: A nonparametric approach. Biometrics 44, 837845 (1988).

Article CAS PubMed MATH Google Scholar

Collins, G. S., Reitsma, J. B., Altman, D. G. & Moons, K. G. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement. Ann. Intern. Med. https://doi.org/10.7326/M14-0697 (2015).

Article PubMed Google Scholar

Clarke, S. et al. Computer-assisted EEG diagnostic review for idiopathic generalized epilepsy. Epilepsy Behav. 121, 106556. https://doi.org/10.1016/j.yebeh.2019.106556 (2019).

Article PubMed Google Scholar

Drake, M. E., Padamadan, H. & Newell, S. A. Interictal quantitative EEG in epilepsy. Seizure Eur. J. Epilepsy 7, 3942 (1998).

Article CAS Google Scholar

Mammone, N. & Morabito, F. C. Analysis of absence seizure EEG via Permutation Entropy spatio-temporal clustering. Int. Jt. Conf. Neural Netw. https://doi.org/10.1109/ijcnn.2011.6033390 (2011).

Article Google Scholar

Lijmer, J. G. et al. Empirical evidence of design-related bias in studies of diagnostic tests. JAMA 282, 10611066 (1999).

Article CAS PubMed Google Scholar

Pepe, M. S., Feng, Z., Janes, H., Bossuyt, P. M. & Potter, J. D. Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: Standards for study design. J. Natl. Cancer Inst. 100, 14321438 (2008).

Article CAS PubMed PubMed Central Google Scholar

Zelig, D. et al. Paroxysmal slow wave events predict epilepsy following a first seizure. Epilepsia 63, 190198 (2022).

Article PubMed Google Scholar

Douw, L. et al. Functional connectivity is a sensitive predictor of epilepsy diagnosis after the first seizure. PLoS ONE 5, e10839 (2010).

Article ADS PubMed PubMed Central Google Scholar

Futoma, J., Simons, M., Panch, T., Doshi-Velez, F. & Celi, L. A. The myth of generalisability in clinical research and machine learning in health care. Lancet Digital Health 2, e489e492 (2020).

Article PubMed Google Scholar

Krumholz, A. et al. Evidence-based guideline: Management of an unprovoked first seizure in adults. Neurology 84, 1705 (2015).

Article PubMed PubMed Central Google Scholar

Gloss, D. et al. Antiseizure medication withdrawal in seizure-free patients: Practice advisory update summary: Report of the AAN guideline subcommittee. Neurology 97, 10721081 (2021).

Article PubMed Google Scholar

Selvitelli, M. F., Walker, L. M., Schomer, D. L. & Chang, B. S. The relationship of interictal epileptiform discharges to clinical epilepsy severity: A study of routine electroencephalograms and review of the literature. J. Clin. Neurophysiol. 27, 8792 (2010).

Article PubMed PubMed Central Google Scholar

Chu, C., Hsu, A.-L., Chou, K.-H., Bandettini, P. & Lin, C. Does feature selection improve classification accuracy? Impact of sample size and feature selection on classification using anatomical magnetic resonance images. Neuroimage 60, 5970 (2012).

Article PubMed Google Scholar

Jollans, L. et al. Quantifying performance of machine learning methods for neuroimaging data. Neuroimage 199, 351365 (2019).

Article PubMed Google Scholar

Fisher, R. S. Bad information in epilepsy care. Epilepsy Behav. 67, 133134 (2017).

Article PubMed Google Scholar

Buchhalter, J. et al. EEG parameters as endpoints in epilepsy clinical trialsAn expert panel opinion paper. Epilepsy Res. 187, 107028 (2022).

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