Microwave breast cancer detection via cost-sensitive ensemble classifiers: Phantom and patient investigation
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- 作者：Yunpeng Li ; yunpeng.li@mail.mcgill.ca" class="auth_mail" title="E-mail the corresponding author ; Emily Porter emily.porter@mail.mcgill.ca" class="auth_mail" title="E-mail the corresponding author ; Adam Santorelli adam.santorelli@mail.mcgill.ca" class="auth_mail" title="E-mail the corresponding author ; Milica Popović milica.popovich@mcgill.ca" class="auth_mail" title="E-mail the corresponding author ; Mark Coates mark.coates@mcgill.ca" class="auth_mail" title="E-mail the corresponding author
- 关键词：Microwave breast cancer detection ; Sensor fusion ; Biomedical monitoring ; Clinical trial ; Ensemble selection
- 刊名：Biomedical Signal Processing and Control
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：31
- 期：Complete
- 页码：366-376
- 全文大小：3484 K
文摘
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The design of three cost-sensitive ensemble classification architectures for the specific application of microwave-based breast cancer detection.
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A principled Neyman–Pearson approach to select algorithmic parameters in order to control the false positive rate while minimizing the false negative rate.
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The performance is assessed thoroughly using both clinical data and phantom data.