Data Mining and Machine Learning Approaches in Breast Cancer Biomedical Research

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Author(s): Gunavathi Chellamuthu (VIT University, India), Kannimuthu S. (Karpagam College of Engineering, India)and Premalatha K. (Bannari Amman Institute of Technology, India)
Copyright: 2019
Pages: 30
Source title: Sentiment Analysis and Knowledge Discovery in Contemporary Business
Source Author(s)/Editor(s): Dharmendra Singh Rajput (VIT University, India), Ramjeevan Singh Thakur (Maulana Azad National Institute of Technology, India)and S. Muzamil Basha (VIT University, India)
DOI: 10.4018/978-1-5225-4999-4.ch011

Keywords: Business and Organizational Research / Business Science Reference / Knowledge Discovery / Library & Information Science

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Abstract

Breast cancer is the most common invasive cancer in females worldwide. Breast cancer diagnosis and breast cancer prognosis are the two important challenges for the researchers in the medical field and also for the practitioners. If the cells in the breast start to grow without any control, it leads to cancer. Normally, the growth of the lump can be seen using x-ray. The benign and malignant breast lumps are distinguished during breast cancer diagnosis. The prognosis process predicts the period at which the breast cancer is likely to reappear in patients who have had their cancers removed. Data mining techniques and machine learning algorithms are mostly used in the whole process of breast cancer diagnosis and treatment. They utilize the large volume of breast cancer data for extracting knowledge. The application of data mining and machine learning methods in biomedical research is presently vital and crucial in efforts to transform intelligently all available data into valuable knowledge.

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Data Mining and Machine Learning Approaches in Breast Cancer Biomedical Research

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