A survey on breast cancer analysis using data mining techniques

• Published in: 2014 IEEE International Conference on Computational Intelligence and Computing Research pp. 1 - 4
• Main Authors: Padmapriya, B., Velmurugan, T.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2014
• Subjects: Breast Cancer Analysis; C4.5 Algorithm; Classification Algorithms; Decision tree; ID3 Algorithm
• ISBN: 1479939749; 9781479939749
• DOI: 10.1109/ICCIC.2014.7238530

Data mining (DM) comprises the core algorithms that enable to gain fundamental insights and knowledge from massive data. In fact, data mining is a part of a larger knowledge discovery process. One of the new researches in data mining application involves analyzing Breast cancer, which are the deadliest disease and most common of all cancers in the leading cause of cancer deaths in women worldwide. Among the various DM techniques, classification plays a vital role in DM research. Breast cancer diagnosis and prognosis are two medical applications pose a great challenge to the researchers in medical field. This survey work analyses the various review and technical articles on breast cancer diagnosis. The main goal of this research is to explore the overview of the current research being carried out using the data mining techniques to enhance the breast cancer diagnosis. Particularly, this survey discusses about use of the classification algorithms ID3 and C4.5 in breast cancer analysis.