Constructing a predictive model for detection of breast cancer

By Fantaye Ayele Ashebo

Breast cancer is the second leading cause of cancer deaths in women now a day and has become the most common cancer among women both in the developed and the developing world. Early detection is the most effective way to decrease breast cancer deaths. But early detection needs an accurate and reliable diagnosis procedure that allows doctors to differentiate benign breast tumors from malignant ones without going for surgical biopsy. Hence, the aim of this research paper is to design a predictive model for breast cancer detection using data mining techniques from breast cancer dataset that is capable of enhancing the reliability of breast cancer disease detection. Data mining techniques may help in answering several important and critical questions by extraction of useful knowledge that support for cost-savings and decision.

• Format: Paperback
• Language: English
• ISBN: 6200487715
• ISBN13: 9786200487711
• Release Date: December 2019
• Publisher: LAP Lambert Academic Publishing
• Length: 112 Pages
• Weight: 0.39 lbs.
• Dimensions: 0.3" x 6.0" x 9.0"