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dc.contributor.authorMourao, Maria Filipapor
dc.contributor.authorBraga, A. C.por
dc.date.accessioned2018-03-19T11:29:11Z-
dc.date.issued2016-
dc.identifier.isbn9783319420844-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://hdl.handle.net/1822/52763-
dc.description.abstractThe Receiver Operating Characteristic (ROC) analysis is a technique that is applied in medical diagnostic testing, especially for discriminating between two health status of a patient: normal (negative) and abnormal (positive). Its ability to compare the performance of different diagnostic systems based on an empirical estimation of the area under the ROC curve (AUC) has made this technique very attractive. Thus, it is important to select an appropriate software program to carry out this comparison. However, this selection has been a difficult task, considering the operational features available in each program. In this work, we aimed to demonstrate how three of the software programs available on the market allow comparing different systems based on AUC indicator, and which tests they use. The features, functionality and performance of the three software programs were evaluated, as well as advantages and disadvantages associated with their use. For illustrative purposes, we used one dataset of the Clinical Risk Index for Babies (CRIB) from Neonatal Intensive Care Units (NICUs) in Portugal.por
dc.description.sponsorshipThe authors would like to thank the availability of the data by the RNMBP team. This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - (Fundação para a Ciência e Tecnologia) within the Project Scope: UID/CEC/00319/2013.por
dc.language.isoengpor
dc.publisherSpringer International Publishing AGpor
dc.relationinfo:eu-repo/grantAgreement/FCT/5876/147280/PTpor
dc.rightsclosedAccesspor
dc.subjectROC curvepor
dc.subjectROCNPApor
dc.subjectComp2ROCpor
dc.subjectStatapor
dc.subjectCRIB (Clinical Risk Index for Babies)por
dc.titleStrengths and Weaknesses of Three Software Programs for the Comparison of Systems Based on ROC Curvespor
dc.typeconferencePaperpor
dc.peerreviewedyespor
oaire.citationStartPage359por
oaire.citationEndPage372por
oaire.citationVolume9786por
dc.date.updated2018-03-14T16:34:39Z-
dc.identifier.doi10.1007/978-3-319-42085-1_28por
dc.description.publicationversioninfo:eu-repo/semantics/publishedVersionpor
dc.subject.wosScience & Technology-
sdum.export.identifier4505-
sdum.journalLecture Notes in Computer Sciencepor
sdum.conferencePublicationCOMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2016, PT Ipor
sdum.bookTitleCOMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2016, PT Ipor
Aparece nas coleções:CAlg - Artigos em livros de atas/Papers in proceedings

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