<doi_batch xmlns="http://www.crossref.org/schema/4.4.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" version="4.4.0"><head><doi_batch_id>fb141b3a-7acc-424a-b9d0-88fb93d9cccd</doi_batch_id><timestamp>20210205102227499</timestamp><depositor><depositor_name>wsea</depositor_name><email_address>mdt@crossref.org</email_address></depositor><registrant>MDT Deposit</registrant></head><body><journal><journal_metadata language="en"><full_title>WSEAS TRANSACTIONS ON BIOLOGY AND BIOMEDICINE</full_title><issn media_type="print">1109-9518</issn><doi_data><doi>10.37394/23208</doi><resource>http://wseas.org/wseas/cms.action?id=4011</resource></doi_data></journal_metadata><journal_issue><publication_date media_type="online"><month>2</month><day>7</day><year>2020</year></publication_date><publication_date media_type="print"><month>2</month><day>7</day><year>2020</year></publication_date><journal_volume><volume>17</volume><doi_data><doi>10.37394/23208.2020.17</doi><resource>http://wseas.org/wseas/cms.action?id=23181</resource></doi_data></journal_volume></journal_issue><journal_article language="en"><titles><title>Data Mining Based Approach for Evaluation of EEG Signals for Epilepsy Detection</title></titles><contributors><person_name sequence="first" contributor_role="author"><given_name>Ayman M.</given_name><surname>Mansour</surname><affiliation>Department of Communication, Electronics and Computer Engineering,  Tafila Technical University, Tafila, 66110, JORDAN</affiliation></person_name><person_name sequence="additional" contributor_role="author"><given_name>Mohammad A.</given_name><surname>Obeidat</surname><affiliation>Department of Power and Mechatronics Engineering,  Tafila Technical University, Tafila, 66110, JORDAN</affiliation></person_name><person_name sequence="additional" contributor_role="author"><given_name>Murad</given_name><surname>Al-Aqtash</surname><affiliation>Department of Communication, Electronics and Computer Engineering,  Tafila Technical University, Tafila, 66110, JORDAN</affiliation></person_name></contributors><jats:abstract xmlns:jats="http://www.ncbi.nlm.nih.gov/JATS1"><jats:p>The objective of this proposed research is to come up with a general methodology for classification of time series events, and to apply that methodology to the analysis of physiological signals recorded from epileptic patients for seizure analysis depending on EEG signal. In contrast to previous works, this research considered an alternative formulation of seizure analysis as a detection problem. This approach offers a good treatment of seizure detection</jats:p></jats:abstract><publication_date media_type="online"><month>5</month><day>18</day><year>2020</year></publication_date><publication_date media_type="print"><month>5</month><day>18</day><year>2020</year></publication_date><pages><first_page>48</first_page><last_page>57</last_page></pages><ai:program xmlns:ai="http://www.crossref.org/AccessIndicators.xsd" name="AccessIndicators"><ai:free_to_read start_date="2020-05-18"/><ai:license_ref applies_to="am" start_date="2020-05-18">https://www.wseas.org/multimedia/journals/biology/2020/a145101-727.pdf</ai:license_ref></ai:program><archive_locations><archive name="Portico"/></archive_locations><doi_data><doi>10.37394/23208.2020.17.7</doi><resource>http://www.wseas.org/multimedia/journals/biology/2020/a145101-727.pdf</resource></doi_data><citation_list><citation key="ref0"><unstructured_citation>www.bEEG-MEG</unstructured_citation></citation><citation key="ref1"><doi>10.1016/s1474-6670(17)33519-x</doi><unstructured_citation>Szilagyi  L.,  Z.benyo,  S.M.  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