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Estimation of risk factors associated with colorectal cancer: an application of knowledge discovery in databases

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dc.contributor.author Firat, Feyza
dc.contributor.author Arslan, Ahmet K.
dc.contributor.author Colak, Cemil
dc.contributor.author Harputluoglu, Hakan
dc.date.accessioned 2019-09-20T10:26:16Z
dc.date.available 2019-09-20T10:26:16Z
dc.date.issued 2016
dc.identifier.citation Firat, F. Arslan, AK. Colak, C . Harputluoglu, H. (2016). Estimation of risk factors associated with colorectal cancer: an application of knowledge discovery in databases. Cilt:43. Sayı:2. 151- 161 ss. tr_TR
dc.identifier.uri http://hdl.handle.net/11616/14177
dc.description.abstract Colorectal cancer is one of the first reasons for death due to cancer in the world. The goal of this study is to predict important risk factors of colorectal cancer (CRC) by knowledge discovery in databases (KDD) methods. This study comprised a retrospective CRC data of patients who had been diagnosed with colorectal cancer. The selected records between 1 January 2010 and 1 March 2014 were collected randomly from Turgut Ozal Medical Centre databases. The study included 160 individuals: 80 patients admitted to Department of Oncology and diagnosed with CRC, and 80 control subjects with non-CRC categorization. The groups were matched for age and gender. We mined retrospective CRC data from large integrated health systems with electronic health records. Specific demographical and clinical variables including calcium, hemoglobin, white blood cells, platelets, potassium, sodium, glucose, creatinine and total bilirubin were used in multilayer perceptron (MLP) artificial neural networks (ANN) modeling. In this study, patient and control groups consist of 160 individuals. In each group, 45 of these (56.3%) are male, and 35 (43.7%) are women. Mean age of CRC patients and control groups is 58.6 +/- 13.0. While the accuracy was 71.31% in training dataset (n=122), the accuracy was 81.82% in testing dataset. Area under curve (AUC) values of training and testing datasets were 0.73 and 0.81, respectively. The suggested MLP ANN model identified significant factors of calcium, creatinine, potassium, platelets, sodium, hemoglobin and total bilirubin. Taken together, the suggested MLP ANN model might be used for the estimation of risk factors associated with CRC as an application of medical KDD. tr_TR
dc.language.iso eng tr_TR
dc.publisher Academıc publıcatıon councıl, po box 17225, khaldıya 72453, kuwaıt tr_TR
dc.rights info:eu-repo/semantics/restrictedAccess tr_TR
dc.subject Eural-networks tr_TR
dc.subject consumptıon tr_TR
dc.subject populatıon tr_TR
dc.subject mortalıty tr_TR
dc.subject platelet tr_TR
dc.subject sodıum tr_TR
dc.title Estimation of risk factors associated with colorectal cancer: an application of knowledge discovery in databases tr_TR
dc.type article tr_TR
dc.relation.journal Kuwaıt journal of scıence tr_TR
dc.contributor.department İnönü Üniversitesi tr_TR
dc.identifier.volume 43 tr_TR
dc.identifier.issue 2 tr_TR
dc.identifier.startpage 151 tr_TR
dc.identifier.endpage 161 tr_TR


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