A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis. (27th June 2017)

• Record Type: Journal Article
• Authors: Cong, Jinyu; Wei, Benzheng; He, Yunlong; Yin, Yilong; Zheng, Yuanjie
• Other Names: Tsui Po-Hsiang Academic Editor.
• Is Part Of: Computational and mathematical methods in medicine. Volume 2017(2017)
• Publication Date: 2017-06-27
• Subjects: Medicine -- Computer simulation -- Periodicals; Medicine -- Mathematical models -- Periodicals; 610.11
• DOI: 10.1155/2017/4896386
• Languages: English
• ISSNs: 1748-670X

Abstract

Abstract : Breast cancer has been one of the main diseases that threatens women's life. Early detection and diagnosis of breast cancer play an important role in reducing mortality of breast cancer. In this paper, we propose a selective ensemble method integrated with the KNN, SVM, and Naive Bayes to diagnose the breast cancer combining ultrasound images with mammography images. Our experimental results have shown that the selective classification method with an accuracy of 88.73% and sensitivity of 97.06% is efficient for breast cancer diagnosis. And indicator R presents a new way to choose the base classifier for ensemble learning.