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Updated: Sep 27, 2025
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Diagnosis of Breast Cancer Pathology on the Wisconsin Dataset with the Help of Data Mining Classification and
Walid Theib Mohammad1, Ronza Teete2, Heyam Al-Aaraj3
1Al-Hussein Bin Talal University, Princess Aisha Bint Al Hussein College for Nursing and Health Sciences, Jordan.
Abstract:
Breast cancer must be addressed by a multidisciplinary team aiming at the patient's comprehensive treatment. Recent advances in science make it possible to evaluate tumor staging and point out the specific treatment. However, these advances must be combined with the availability of resources and the easy operability of the technique. This study is aimed at distinguishing and classifying benign and malignant cells, which are tumor types, from the data on the Wisconsin Diagnostic Breast Cancer (WDBC) dataset by applying data mining classification and clustering techniques with the help of the Weka tool. In addition, various algorithms and techniques used in data mining were measured with success percentages, and the most successful ones on the dataset were determined and compared with each other.
