{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T11:52:13Z","timestamp":1773057133731,"version":"3.50.1"},"reference-count":71,"publisher":"Wiley","license":[{"start":{"date-parts":[[2022,1,20]],"date-time":"2022-01-20T00:00:00Z","timestamp":1642636800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2022,1,20]]},"abstract":"<jats:p>Epileptic seizures occur due to brain abnormalities that can indirectly affect patient\u2019s health. It occurs abruptly without any symptoms and thus increases the mortality rate of humans. Almost 1% of world\u2019s population suffers from epileptic seizures. Prediction of seizures before the beginning of onset is beneficial for preventing seizures by medication. Nowadays, modern computational tools, machine learning, and deep learning methods have been used to predict seizures using EEG. However, EEG signals may get corrupted with background noise, and artifacts such as eye blinks and physical movements of muscles may lead to \u201cpops\u201d in the signal, resulting in electrical interference, which is cumbersome to detect through visual inspection for longer duration recordings. These limitations in automatic detection of interictal spikes and epileptic seizures are preferred, which is an essential tool for examining and scrutinizing the EEG recording more precisely. These restrictions bring our attention to present a review of automated schemes that will help neurologists categorize epileptic and nonepileptic signals. While preparing this review paper, it is observed that feature selection and classification are the main challenges in epilepsy prediction algorithms. This paper presents various techniques depending on various features and classifiers over the last few years. The methods presented will give a detailed understanding and ideas about seizure prediction and future research directions.<\/jats:p>","DOI":"10.1155\/2022\/7751263","type":"journal-article","created":{"date-parts":[[2022,1,21]],"date-time":"2022-01-21T01:35:21Z","timestamp":1642728921000},"page":"1-17","source":"Crossref","is-referenced-by-count":68,"title":["Review on Epileptic Seizure Prediction: Machine Learning and Deep Learning Approaches"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4080-4949","authenticated-orcid":true,"given":"Milind","family":"Natu","sequence":"first","affiliation":[{"name":"Department of Electronics and Telecommunication, Symbiosis Institute of Technology, Symbiosis International (Deemed University), SIU, Lavale, Pune, Maharashtra, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6647-9347","authenticated-orcid":true,"given":"Mrinal","family":"Bachute","sequence":"additional","affiliation":[{"name":"Symbiosis Institute of Technology (SIT), Symbiosis International (Deemed University), SIU, Lavale, Pune, Maharashtra, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3882-7030","authenticated-orcid":true,"given":"Shilpa","family":"Gite","sequence":"additional","affiliation":[{"name":"Computer Science and Information Technology Department, Symbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune 412115, India"},{"name":"Symbiosis Centre of Applied AI (SCAAI), Symbiosis International (Deemed) University, Pune 412115, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2653-3780","authenticated-orcid":true,"given":"Ketan","family":"Kotecha","sequence":"additional","affiliation":[{"name":"Computer Science and Information Technology Department, Symbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune 412115, India"},{"name":"Symbiosis Centre of Applied AI (SCAAI), Symbiosis International (Deemed) University, Pune 412115, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8026-4246","authenticated-orcid":true,"given":"Ankit","family":"Vidyarthi","sequence":"additional","affiliation":[{"name":"Department of CSE&IT, Jaypee Institute of Information Technology Noida, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1528-1167.2009.02481.x"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2010.2048568"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.32598\/bcn.9.4.227"},{"issue":"2","key":"4","article-title":"Fatal status epilepticus: a clinico-pathological analysis among 100 patients: from a developing country perspective","volume":"91","author":"S. 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