A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis
Joint Authors
Yin, Yilong
Zheng, Yuanjie
He, Yunlong
Cong, Jinyu
Wei, Benzheng
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-06-27
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Cong, Jinyu& Wei, Benzheng& He, Yunlong& Yin, Yilong& Zheng, Yuanjie. 2017. A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis. Computational and Mathematical Methods in Medicine،Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1142151
Modern Language Association (MLA)
Cong, Jinyu…[et al.]. A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis. Computational and Mathematical Methods in Medicine No. 2017 (2017), pp.1-7.
https://search.emarefa.net/detail/BIM-1142151
American Medical Association (AMA)
Cong, Jinyu& Wei, Benzheng& He, Yunlong& Yin, Yilong& Zheng, Yuanjie. A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis. Computational and Mathematical Methods in Medicine. 2017. Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1142151
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142151