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Partial Least Squares (PLS) Methods for Abnormal Detection of Breast Cells

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Data Science (ICPCSEE 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 727))

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Abstract

Breast cancer is one of the malignant tumors having high incidence in women, the incidence of breast cancer has increased in all parts of the world since twentieth century, but its etiology is not yet completely clear, so it is very important to detect breast cells. In this paper, we built a regression model to detect breast cells, and generated a method for predicting the formation of benign and malignant breast cells by training the model, then we used the 10 features of breast cells to predict it, the results reaching upto 93.67% accuracy, it was very effective to predict and analyse whether the breast cells getting cancer, It had an important role in the diagnosis and prevention of breast cancer.

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Acknowledgments

This study was supported by the National Natural Science Foundation of China (61170192, 41271292), China Postdoctoral Science Foundation (No. 2015M580765), Chongqing Postdoctoral Science Foundation (No. Xm2016041), Scientific and Technological Research Program of Chongqing Municipal Education Commission (KJ1603109, KJ1503207), the Fundamental Research Funds for the Central Universities (XDJK2014C039, XDJK2016C045), Doctoral Fund of Southwestern University (swu1114033).

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Authors and Affiliations

  1. School of Computer and Information Science, Southwest University, Chongqing, 400715, China

    Yuchen Zhu, Shanxiong Chen, Chunrong Chen & Lin Chen

Authors
  1. Yuchen Zhu
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  2. Shanxiong Chen
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  3. Chunrong Chen
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  4. Lin Chen
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Corresponding author

Correspondence to Shanxiong Chen .

Editor information

Editors and Affiliations

  1. Central South University, Changsha, China

    Beiji Zou

  2. Central South University, Changsha, China

    Min Li

  3. Harbin Institute of Technology, Harbin, China

    Hongzhi Wang

  4. Harbin University of Science and Technology, Harbin, China

    Xianhua Song

  5. Harbin University of Science and Technology, Harbin, China

    Wei Xie

  6. Harbin Sea of Clouds and Computer Technology, Harbin, China

    Zeguang Lu

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Zhu, Y., Chen, S., Chen, C., Chen, L. (2017). Partial Least Squares (PLS) Methods for Abnormal Detection of Breast Cells. In: Zou, B., Li, M., Wang, H., Song, X., Xie, W., Lu, Z. (eds) Data Science. ICPCSEE 2017. Communications in Computer and Information Science, vol 727. Springer, Singapore. https://doi.org/10.1007/978-981-10-6385-5_8

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  • DOI: https://doi.org/10.1007/978-981-10-6385-5_8

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6384-8

  • Online ISBN: 978-981-10-6385-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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