Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/11934
Title: Prediction models for estimation of survival rate and relapse for breast cancer patients
Authors: Andjelkovic Cirkovic, Bojana
Cvetkovic, Aleksandar
Ninkovic, Srdjan
Filipovic, Nenad
Issue Date: 2015
Abstract: © 2015 IEEE. In this paper, we described the practical application of data mining methods for estimation of survival rate and disease relapse for breast cancer patients. A comparative study of prominent machine learning models was carried out and according to the achieved results we concluded that the classifiers obviously learn some of the concepts of breast cancer survivability and recurrence. These algorithms were successfully applied to a novel breast cancer data set of the Clinical Center of Kragujevac. The Naive Bayes classifier is selected as a model for prognosis of cancer survivability on the basis of the 5 years survival rate, while the Artificial Neural Network has achieved the best performance in prognosis of cancer recurrence. Selection of twenty attributes that are the most related to success of prognosis on survivability can give new insights into the set of prognostic factors which need to be observed by medical experts.
URI: https://scidar.kg.ac.rs/handle/123456789/11934
Type: conferenceObject
DOI: 10.1109/BIBE.2015.7367658
SCOPUS: 2-s2.0-84962860754
Appears in Collections:Faculty of Engineering, Kragujevac
Faculty of Medical Sciences, Kragujevac

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