Comparative performance analysis of machine learning classifiers in detection of childhood pneumonia using chest radiographs

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dc.creatorSousa, Rafael Teixeira
dc.creatorMarques, Oge
dc.creatorSoares, Fabrizzio Alphonsus Alves de Melo Nunes
dc.creatorSene Júnior, Iwens Gervasio
dc.creatorOliveira, Leandro Luis Galdino de
dc.creatorSpoto, Edmundo Sérgio
dc.date.accessioned2018-05-23T15:55:33Z
dc.date.available2018-05-23T15:55:33Z
dc.date.issued2013
dc.description.abstractThis work extends PneumoCAD, a Computer-Aided Diagnosis system for detecting pneumonia in infants using radiographic images [1], with the aim of improving the system’s accuracy and robustness. We implement and compare three contemporary machine learning classifiers, namely: Na¨ıve Bayes, K-Nearest Neighbor (KNN), and Support Vector Machines (SVM). Results of our experiments demonstrate that the SVM classifier produces the best overall results.pt_BR
dc.identifier.citationSOUSA, Rafael T.; MARQUES, Oge; SOARES, Fabrizzio Alphonsus A. M. N.; SENE JÚNIOR, Iwens I. G.; OLIVEIRA, Leandro L. G.; SPOTO, Edmundo S. Comparative performance analysis of machine learning classifiers in detection of childhood pneumonia using chest radiographs. Procedia Computer Science, New York, v. 18, n. 2013, p. 2579-2582, 2013.pt_BR
dc.identifier.doi10.1016/j.procs.2013.05.444
dc.identifier.issne- 1877-0509
dc.identifier.urihttp://repositorio.bc.ufg.br/handle/ri/15079
dc.language.isoengpt_BR
dc.publisher.countryEstados unidospt_BR
dc.publisher.departmentInstituto de Informática - INF (RG)pt_BR
dc.rightsAcesso Abertopt_BR
dc.subjectMachine Learningpt_BR
dc.subjectComputer-aided diagnosis (CAD)pt_BR
dc.subjectChildhood pneumoniapt_BR
dc.titleComparative performance analysis of machine learning classifiers in detection of childhood pneumonia using chest radiographspt_BR
dc.typeArtigopt_BR

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