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Research on Data Mining Method for Breast Cancer Case Data

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Cloud Computing and Security (ICCCS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11064))

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Abstract

With the development of computer technology, medical institutions not only treat patients using advanced instruments but can also improve the collection and storage of patient medical records. We used distributed cloud data platforms to obtain case data of breast cancer patients from different medical institutions and quantified the text data based on a physician’s advice. We then processed the data using a common classification algorithm, predicted each patient’s survival, and compared the accuracy of different algorithms. Our experimental results show that the locally weighted learning (LWL) algorithm has high accuracy and precision, indicating that the LWL algorithm is a good way to predict breast cancer patient survival.

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Authors and Affiliations

  1. Network Information Center, Binzhou Medical University, Yantai, 264003, China

    Yanning Cao

  2. School of Basic Medical Sciences, Binzhou Medical University, Yantai, 264003, China

    Xiaoshu Zhang

Authors
  1. Yanning Cao
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  2. Xiaoshu Zhang
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Corresponding author

Correspondence to Xiaoshu Zhang .

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Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Zhaoqing Pan

  3. Department of Computer Science, Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Cao, Y., Zhang, X. (2018). Research on Data Mining Method for Breast Cancer Case Data. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11064. Springer, Cham. https://doi.org/10.1007/978-3-030-00009-7_7

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  • DOI: https://doi.org/10.1007/978-3-030-00009-7_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00008-0

  • Online ISBN: 978-3-030-00009-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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