Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/65882

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dc.contributor.authorMachado, José Manuelpor
dc.contributor.authorCardoso, Ana Catarinapor
dc.contributor.authorGomes, Inês Varelapor
dc.contributor.authorSilva, Inêspor
dc.contributor.authorLopes, Vítorpor
dc.contributor.authorPeixoto, Hugopor
dc.contributor.authorAbelha, Antóniopor
dc.date.accessioned2020-07-07T21:42:34Z-
dc.date.issued2019-
dc.identifier.isbn9783030118891por
dc.identifier.issn2194-5357-
dc.identifier.urihttps://hdl.handle.net/1822/65882-
dc.description.abstractThe management of peptic ulcer disease usually implies an urgent surgical procedure with the need of a patient’s hospital admission. By predicting the length of hospital stay of patients, improvements can be made regarding the quality of services provided to patients. This paper focuses on using real data to identify patterns in patients’ profiles and surgical events, in order to predict if patients will need hospital care for a shorter or longer period of time. This goal is pursued using a Data Mining process which follows the CRISP-DM methodology. In particular, classification models are built by combining different scenarios, algorithms and sampling methods. The data mining model which performed best achieved an accuracy of 87.30%, a specificity of 89.40%, and a sensitivity of 81.30%, using JRip, a rule-based algorithm and Cross Validation as a sampling method.por
dc.description.sponsorshipFCT - Fundação para a Ciência e a Tecnologia (UID/CEC/00319/2013)por
dc.language.isoengpor
dc.publisherSpringer Verlagpor
dc.relationinfo:eu-repo/grantAgreement/FCT/5876/147280/PTpor
dc.rightsrestrictedAccesspor
dc.subjectClassificationpor
dc.subjectCRISP-DMpor
dc.subjectData miningpor
dc.subjectDecision Support Systemspor
dc.subjectLength of hospital staypor
dc.subjectPerforated peptic ulcerpor
dc.titlePredicting the length of hospital stay after surgery for perforated peptic ulcerpor
dc.typeconferencePaperpor
dc.peerreviewedyespor
oaire.citationStartPage569por
oaire.citationEndPage579por
oaire.citationVolume918por
dc.date.updated2020-07-07T18:14:43Z-
dc.identifier.doi10.1007/978-3-030-11890-7_55por
dc.date.embargo10000-01-01-
sdum.export.identifier5613-
sdum.journalAdvances in Intelligent Systems and Computingpor
oaire.versionPpor
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