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28 September 2016 Preprocessing for classification of thermograms in breast cancer detection
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Proceedings Volume 10031, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2016; 100313A (2016) https://doi.org/10.1117/12.2249307
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2016, 2016, Wilga, Poland
Abstract
Performance of binary classification of breast cancer suffers from high imbalance between classes. In this article we present the preprocessing module designed to negate the discrepancy in training examples. Preprocessing module is based on standardization, Synthetic Minority Oversampling Technique and undersampling. We show how each algorithm influences classification accuracy. Results indicate that described module improves overall Area Under Curve up to 10% on the tested dataset. Furthermore we propose other methods of dealing with imbalanced datasets in breast cancer classification.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Łukasz Neumann, Robert M. Nowak, Rafał Okuniewski, Witold Oleszkiewicz, Paweł Cichosz, Dariusz Jagodziński, and Mateusz Matysiewicz "Preprocessing for classification of thermograms in breast cancer detection", Proc. SPIE 10031, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2016, 100313A (28 September 2016); https://doi.org/10.1117/12.2249307
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