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dc.contributor.authorKaya, Aydın
dc.contributor.authorCan, Ahmet Burak
dc.date.accessioned2019-12-13T06:51:39Z
dc.date.available2019-12-13T06:51:39Z
dc.date.issued2015
dc.identifier.issn1532-0464
dc.identifier.urihttps://doi.org/10.1016/j.jbi.2015.05.011
dc.identifier.urihttp://hdl.handle.net/11655/18656
dc.description.abstractPredicting malignancy of solitary pulmonary nodules from computer tomography scans is a difficult and important problem in the diagnosis of lung cancer. This paper investigates the contribution of nodule characteristics in the prediction of malignancy. Using data from Lung Image Database Consortium (LIDC) database, we propose a weighted rule based classification approach for predicting malignancy of pulmonary nodules. LIDC database contains CT scans of nodules and information about nodule characteristics evaluated by multiple annotators. In the first step of our method, votes for nodule characteristics are obtained from ensemble classifiers by using image features. In the second step, votes and rules obtained from radiologist evaluations are used by a weighted rule based method to predict malignancy. The rule based method is constructed by using radiologist evaluations on previous cases. Correlations between malignancy and other nodule characteristics and agreement ratio of radiologists are considered in rule evaluation. To handle the unbalanced nature of LIDC, ensemble classifiers and data balancing methods are used. The proposed approach is compared with the classification methods trained on image features. Classification accuracy, specificity and sensitivity of classifiers are measured. The experimental results show that using nodule characteristics for malignancy prediction can improve classification results. (C) 2015 Elsevier Inc. All rights reserved.
dc.language.isoen
dc.publisherAcademic Press Inc Elsevier Science
dc.relation.isversionof10.1016/j.jbi.2015.05.011
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectComputer Science
dc.subjectMedical Informatics
dc.titleA Weighted Rule Based Method for Predicting Malignancy of Pulmonary Nodules By Nodule Characteristics
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.relation.journalJournal Of Biomedical Informatics
dc.contributor.departmentBilgisayar Mühendisliği
dc.identifier.volume56
dc.identifier.startpage69
dc.identifier.endpage79
dc.indexingWoS
dc.indexingScopus


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