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Predicting Xerostomia induced by IMRT treatments: A logistic regression approach

dc.contributor.authorSoares, Inês
dc.contributor.authorDias, Joana
dc.contributor.authorRocha, Humberto
dc.contributor.authorLopes, Maria do Carmo
dc.contributor.authorCosta Ferreira, Brigida
dc.date.accessioned2015-01-28T15:47:12Z
dc.date.available2015-01-28T15:47:12Z
dc.date.issued2014
dc.description.abstractRadiotherapy is one of the main treatments used against cancer. Radiotherapy uses radiation to destroy cancerous cells trying, at the same time, to minimize the damages in healthy tissues. The planning of a radiotherapy treatment is patient dependent, resulting in a lengthy trial and error procedure until a treatment complying as most as possible with the medical prescription is found. Intensity Modulated Radiation Therapy (IMRT) is one technique of radiation treatment that allows the achievement of a high degree of conformity between the area to be treated and the dose absorbed by healthy tissues. Nevertheless, it is still not possible to eliminate completely the potential treatments’ side-effects. In this retrospective study we use the clinical data from patients with head-and-neck cancer treated at the Portuguese Institute of Oncology of Coimbra and explore the possibility of classifying new and untreated patients according to the probability of xerostomia 12 months after the beginning of IMRT treatments by using a logistic regression approach. The results obtained show that the classifier presents a high discriminative ability in predicting the binary response “at risk for xerostomia at 12 months”por
dc.identifier.doi10.1109/BIBM.2014.6999271
dc.identifier.urihttp://hdl.handle.net/10400.22/5501
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisher2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)por
dc.subjectRadiotherapypor
dc.subjectIMRTpor
dc.subjectlogistic regression predictorspor
dc.subjectROC curvespor
dc.subjectAUCpor
dc.titlePredicting Xerostomia induced by IMRT treatments: A logistic regression approachpor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceBelfast, United Kingdompor
oaire.citation.endPage77por
oaire.citation.startPage72por
oaire.citation.title2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)por
person.familyNameCosta Ferreira
person.givenNameBrigida
person.identifier1167997
person.identifier.ciencia-idA61B-E07B-84B3
person.identifier.orcid0000-0001-7988-7545
person.identifier.scopus-author-id14050253300
rcaap.rightsopenAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublicationeac8b2c3-0ef3-48f5-a3c7-8ca796a098ae
relation.isAuthorOfPublication.latestForDiscoveryeac8b2c3-0ef3-48f5-a3c7-8ca796a098ae

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