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Radial basis function neural networks versus fuzzy models to predict return of consciousness after general anesthesia

2004Conference object Restricted access
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dc.contributor.authorNunes, Catarina S.
dc.contributor.authorMendonca, T. F.
dc.contributor.authorAmorim, Pedro
dc.contributor.authorFerreira, D. A.
dc.contributor.authorAntunes, L. M.
dc.date.accessioned2023-05-31T14:17:38Z
dc.date.available2023-05-31T14:17:38Z
dc.date.issued2004
dc.description.abstractThis paper presents two modelling techniques to predict return of consciousness (ROC) after general anaesthesia, considering the effect concentration of the anaesthetic drug at awakening. First, several clinical variables were statistically analysed to determine their correlation with the awakening concentration. The anaesthetic and the analgesic mean dose during surgery, and the age of the patient, proved to have significantly high correlation coefficients. Variables like the mean bispectral index value during surgery, duration of surgery did not present a statistical relation with ROC. Radial basis function (RBF) neural networks were trained relating different sets of clinical values with the anaesthetic drug effect concentration at awakening. Secondly, fuzzy models were built using an Adaptive Network-Based Fuzzy Inference System (ANFIS) also relating different sets of variables. Clinical data was used to train and test the models. The fuzzy models and RBF neural networks proved to have good prediction properties and balanced results.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationC. S. Nunes, T. F. Mendonca, P. Amorim, D. A. Ferreira and L. M. Antunes, "Radial basis function neural networks versus fuzzy models to predict return of consciousness after general anesthesia," The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Francisco, CA, USA, 2004, pp. 865-868pt_PT
dc.identifier.doi10.1109/IEMBS.2004.1403295pt_PT
dc.identifier.isbn0-7803-8439-3
dc.identifier.pmid17271814
dc.identifier.urihttp://hdl.handle.net/10400.2/13937
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherIEEEpt_PT
dc.subjectNeural networkspt_PT
dc.subjectANFISpt_PT
dc.subjectFuzzy modelspt_PT
dc.subjectAnesthesiapt_PT
dc.subjectPredictionpt_PT
dc.titleRadial basis function neural networks versus fuzzy models to predict return of consciousness after general anesthesiapt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceSan Francisco, CA, USApt_PT
oaire.citation.endPage868pt_PT
oaire.citation.startPage865pt_PT
oaire.citation.titleThe 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Societypt_PT
oaire.citation.volume3pt_PT
person.familyNameNunes
person.familyNameAmorim
person.givenNameCatarina S.
person.givenNamePedro
person.identifier.ciencia-id691F-CDC2-E26A
person.identifier.orcid0000-0002-8357-0994
person.identifier.orcid0000-0001-7466-4174
person.identifier.scopus-author-id55429654100
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationcc3069ec-f930-455f-9226-b77e5d2dc14b
relation.isAuthorOfPublication1ef321dd-4f09-493c-b801-e9a99b28947d
relation.isAuthorOfPublication.latestForDiscoverycc3069ec-f930-455f-9226-b77e5d2dc14b

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