A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis

A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis

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 t...

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Main Authors: Jinyu Cong, Benzheng Wei, Yunlong He, Yilong Yin, Yuanjie Zheng
Format: Article
Language:English
Published: Hindawi Limited 2017-01-01
Series:Computational and Mathematical Methods in Medicine
Online Access:http://dx.doi.org/10.1155/2017/4896386
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spelling doaj-dac08f2629914ede953ba8fb13ef44022020-11-25T00:20:40ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182017-01-01201710.1155/2017/48963864896386A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer DiagnosisJinyu Cong0Benzheng Wei1Yunlong He2Yilong Yin3Yuanjie Zheng4School of Information Science and Engineering, Key Lab of Intelligent Computing & Information Security in Universities of Shandong, Institute of Life Sciences, Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology, and Key Lab of Intelligent Information Processing, Shandong Normal University, Jinan 250358, ChinaCollege of Science and Technology, Shandong University of Traditional Chinese Medicine, Jinan 250014, ChinaSchool of Information Science and Engineering, Key Lab of Intelligent Computing & Information Security in Universities of Shandong, Institute of Life Sciences, Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology, and Key Lab of Intelligent Information Processing, Shandong Normal University, Jinan 250358, ChinaSchool of Computer Science and Technology, Shandong University, Jinan 250100, ChinaSchool of Information Science and Engineering, Key Lab of Intelligent Computing & Information Security in Universities of Shandong, Institute of Life Sciences, Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology, and Key Lab of Intelligent Information Processing, Shandong Normal University, Jinan 250358, ChinaBreast 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.http://dx.doi.org/10.1155/2017/4896386
collection DOAJ
language English
format Article
sources DOAJ
author Jinyu Cong
Benzheng Wei
Yunlong He
Yilong Yin
Yuanjie Zheng
spellingShingle Jinyu Cong
Benzheng Wei
Yunlong He
Yilong Yin
Yuanjie Zheng
A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis
Computational and Mathematical Methods in Medicine
author_facet Jinyu Cong
Benzheng Wei
Yunlong He
Yilong Yin
Yuanjie Zheng
author_sort Jinyu Cong
title A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis
title_short A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis
title_full A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis
title_fullStr A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis
title_full_unstemmed A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis
title_sort selective ensemble classification method combining mammography images with ultrasound images for breast cancer diagnosis
publisher Hindawi Limited
series Computational and Mathematical Methods in Medicine
issn 1748-670X
1748-6718
publishDate 2017-01-01
description 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.
url http://dx.doi.org/10.1155/2017/4896386
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