Quantitative preterm EEG analysis: The need for caution in using modern data science techniques

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dc.contributor.author O'Toole, John M.
dc.contributor.author Boylan, Geraldine B.
dc.date.accessioned 2019-11-19T12:04:27Z
dc.date.available 2019-11-19T12:04:27Z
dc.date.issued 2019-05-03
dc.identifier.citation Boylan, G.B. and O'Toole, J.M., 2019. Quantitative preterm EEG analysis: the need for caution in using modern data science techniques. Frontiers in pediatrics, 7, (174). DOI:10.3389/fped.2019.00174 en
dc.identifier.volume 7 en
dc.identifier.startpage 1 en
dc.identifier.endpage 11 en
dc.identifier.uri http://hdl.handle.net/10468/9075
dc.identifier.doi 10.3389/fped.2019.00174 en
dc.description.abstract Haemodynamic changes during neonatal transition increase the vulnerability of the preterm brain to injury. Real-time monitoring of brain function during this period would help identify the immediate impact of these changes on the brain. Neonatal EEG provides detailed real-time information about newborn brain function but can be difficult to interpret for non-experts; preterm neonatal EEG poses even greater challenges. An objective quantitative measure of preterm brain health would be invaluable during neonatal transition to help guide supportive care and ultimately protect the brain. Appropriate quantitative measures of preterm EEG must be calculated and care needs to be taken when applying the many techniques available for this task in the era of modern data science. This review provides valuable information about the factors that influence quantitative EEG analysis and describes the common pitfalls. Careful feature selection is required and attention must be paid to behavioural state given the variations encountered in newborn EEG during different states. Finally, the detrimental influence of artefacts on quantitative EEG analysis is illustrated. en
dc.description.sponsorship 15/SIRG/3580 en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Frontiers Media en
dc.relation.uri https://www.frontiersin.org/articles/10.3389/fped.2019.00174
dc.rights © 2019 O'Toole and Boylan en
dc.rights.uri https://creativecommons.org/licenses/by/4.0/ en
dc.subject EEG analysis en
dc.subject Preterm en
dc.subject Neonatal en
dc.subject Data science techniques en
dc.title Quantitative preterm EEG analysis: The need for caution in using modern data science techniques en
dc.type Article (peer-reviewed) en
dc.internal.authorcontactother Geraldine Boylan, Department of Paediatrics and Child Health, University College Cork, Cork, Ireland. +353-21-490-3000 Email: g.boylan@ucc.ie en
dc.internal.availability Full text available en
dc.description.version Published Version en
dc.contributor.funder Science Foundation Ireland en
dc.description.status Peer reviewed en
dc.identifier.journaltitle Frontiers in Pediatrics en
dc.internal.IRISemailaddress g.boylan@ucc.ie en
dc.identifier.articleid 174 en
dc.relation.project info:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2272/IE/Irish Centre for Fetal and Neonatal Translational Research (INFANT)/ en
dc.identifier.eissn 2296-2360

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© 2019 O'Toole and Boylan Except where otherwise noted, this item's license is described as © 2019 O'Toole and Boylan
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