Computer aided breast cancer diagnosis system with fuzzy multiple-parameter support vector machine

Author:

Pack Chulwoo1,Shin Sung1,Son Seong Ho2,Jeon Soon Ik2

Affiliation:

1. South Dakota State University, Brookings, SD

2. Electronics and Telecommunications Research Institute (ETRI), DaeJeon, South Korea

Publisher

ACM

Reference16 articles.

1. World Health Organization. (2014 Sep 10). U.S. Available: http://www.who.int/cancer/detection/breastcancer/en/ World Health Organization. (2014 Sep 10). U.S. Available: http://www.who.int/cancer/detection/breastcancer/en/

2. Computer-Aided Diagnosis of Malignant Mammograms using Zernike Moments and SVM

3. Computer-Aided Detection (CAD) in Screening Mammography:Sensitivity of Commercial CAD Systems for Detecting Architectural Distortion

4. Study of wireless mammography image transmission impacts on robust cyber-aided diagnosis systems

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1. A review on machine learning techniques for the assessment of image grading in breast mammogram;International Journal of Machine Learning and Cybernetics;2022-04-01

2. A Comprehensive Study of Mammogram Classification Techniques;Intelligent Systems Reference Library;2021-07-15

3. A computer-aided approach for automatic detection of breast masses in digital mammogram via spectral clustering and support vector machine;Physical and Engineering Sciences in Medicine;2021-02-12

4. A systematic map of data analytics in breast cancer;Proceedings of the Australasian Computer Science Week Multiconference;2018-01-29

5. Enhanced Breast Cancer Classification with Automatic Thresholding Using SVM and Harris Corner Detection;Proceedings of the International Conference on Research in Adaptive and Convergent Systems;2016-10-11

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