ENHANCING BREAST CANCER DETECTION USING DATA MINING CLASSIFICATION TECHNIQUES

Year 2017, , 310 - 316, 30.06.2017

Florije Ismaili Luzana Shabani Bujar Raufi Jaumin Ajdari Xhemal Zenuni

https://doi.org/10.17261/Pressacademia.2017.605

Abstract

Cancer is one of the crucial causes of death for both men and
women. All over the world, breast cancer is one of the leading cause of cancer
deaths in women. The most effective way to reduce cancer death is to detect it
earlier but the detection of cancer in early stages is not an easy process. As
result, many researches are focused on developing different systems for breast
cancer detection. In this paper we have discussed various data mining
approaches that have been utilized for breast cancer diagnosis and prognosis.
We have proposed a breast cancer prediction framework consisting of four main
modules: Data Collection, Data Preprocessing, Feature Selection, and
Classification. Evaluation results are provided as well. The goal is to find
the best combination for feature extraction algorithm and classification
algorithm, which will improve the accuracy of mammograms classification
process.

 

Keywords

Breast cancer, mammograms classification, data mining

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