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Sleepiness should be reinvestigated through the lens of clinical neurophysiology: A mixed expertal and big-data Natural Language Processing approach

dc.rights.licenseopenen_US
dc.contributor.authorMARTIN, Vincent P.
dc.contributor.authorGAULD, Christophe
hal.structure.identifierSommeil, Addiction et Neuropsychiatrie [Bordeaux] [SANPSY]
dc.contributor.authorTAILLARD, Jacques
ORCID: 0000-0001-9067-8189
IDREF: 229930786
dc.contributor.authorPETER-DEREX, Laure
dc.contributor.authorLOPEZ, Régis
hal.structure.identifierSommeil, Addiction et Neuropsychiatrie [Bordeaux] [SANPSY]
dc.contributor.authorMICOULAUD-FRANCHI, Jean-Arthur
dc.date.accessioned2025-09-01T13:47:46Z
dc.date.available2025-09-01T13:47:46Z
dc.date.issued2024-04
dc.identifier.issn0987-7053en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/207548
dc.description.abstractEnHistorically, the field of sleep medicine has revolved around electrophysiological tools. However, the use of these tools as a neurophysiological method of investigation seems to be underrepresented today, from both international recommendations and sleep centers, in contrast to behavioral and psychometric tools. The aim of this article is to combine a data-driven approach and neurophysiological and sleep medicine expertise to confirm or refute the hypothesis that neurophysiology has declined in favor of behavioral or self-reported dimensions in sleep medicine for the investigation of sleepiness, despite the use of electrophysiological tools. Using Natural Language Processing methods, we analyzed the abstracts of the 18,370 articles indexed by PubMed containing the terms 'sleepiness' or 'sleepy' in the title, abstract, or keywords. For this purpose, we examined these abstracts using two methods: a lexical network, enabling the identification of concepts (neurophysiological or clinical) related to sleepiness in these articles and their interconnections; furthermore, we analyzed the temporal evolution of these concepts to extract historical trends. These results confirm the hypothesis that neurophysiology has declined in favor of behavioral or self-reported dimensions in sleep medicine for the investigation of sleepiness. In order to bring sleepiness measurements closer to brain functioning and to reintroduce neurophysiology into sleep medicine, we discuss two strategies: the first is reanalyzing electrophysiological signals collected during the standard sleep electrophysiological test; the second takes advantage of the current trend towards dimensional models of sleepiness to situate clinical neurophysiology at the heart of the redefinition of sleepiness.
dc.language.isoENen_US
dc.subject.enNatural language processing
dc.subject.enNeurophysiology
dc.subject.enSleep medicine
dc.subject.enSleepiness
dc.subject.enText mining
dc.title.enSleepiness should be reinvestigated through the lens of clinical neurophysiology: A mixed expertal and big-data Natural Language Processing approach
dc.title.alternativeNeurophysiol Clinen_US
dc.typeArticle de revueen_US
dc.identifier.doi10.1016/j.neucli.2023.102937en_US
dc.subject.halSciences du Vivant [q-bio]/Neurosciences [q-bio.NC]en_US
dc.identifier.pubmed38401240en_US
bordeaux.journalNeurophysiologie Cliniqueen_US
bordeaux.page102937en_US
bordeaux.volume54en_US
bordeaux.hal.laboratoriesSANPSY (Sommeil, Addiction, Neuropsychiatrie) - UMR 6033en_US
bordeaux.issue2en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionCNRSen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.import.sourcecrossref
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exportfalse
workflow.import.sourcecrossref
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Neurophysiologie%20Clinique&rft.date=2024-04&rft.volume=54&rft.issue=2&rft.spage=102937&rft.epage=102937&rft.eissn=0987-7053&rft.issn=0987-7053&rft.au=MARTIN,%20Vincent%20P.&GAULD,%20Christophe&TAILLARD,%20Jacques&PETER-DEREX,%20Laure&LOPEZ,%20R%C3%A9gis&rft.genre=article


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