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International Conference on Future Data and Security Engineering

FDSE 2020: Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications pp 294–308Cite as

Inflammatory Bowel Disease Classification Improvement with Metagenomic Data Binning Using Mean-Shift Clustering

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1306))

Abstract

In the human body, where the greatest concentration of bacteria is the gastrointestinal tract, it is considered to be a diverse and complex microbial population, involving many different diseases. The development of metagenomics has many achievements in evolution and biodiversity. The application of machine learning algorithms to solve metagenomics problems has helped researchers make new advances in the field of personalized medicine, especially the diagnosis and improvement of human health people. In this study, we propose an unattended binning approach combined with Mean-shift algorithm to improve predictive performance. We performed on the Inflammatory Bowel Disease (IDB) dataset with 6 subclasses. This clustering method has improved results when applying deep learning techniques and shows the promising potential of data preprocessing methods when applied on different datasets.

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Authors and Affiliations

  1. College of Information and Communication Technology, Can Tho University, Can Tho, Vietnam

    Nhi Yen Kim Phan & Hai Thanh Nguyen

Authors
  1. Nhi Yen Kim Phan
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  2. Hai Thanh Nguyen
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Corresponding author

Correspondence to Hai Thanh Nguyen .

Editor information

Editors and Affiliations

  1. Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam

    Tran Khanh Dang

  2. Johannes Kepler University of Linz, Linz, Austria

    Josef Küng

  3. Hosei University, Tokyo, Japan

    Makoto Takizawa

  4. Sungkyunkwan University, Suwon, Korea (Republic of)

    Tai M. Chung

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Phan, N.Y.K., Nguyen, H.T. (2020). Inflammatory Bowel Disease Classification Improvement with Metagenomic Data Binning Using Mean-Shift Clustering. In: Dang, T.K., Küng, J., Takizawa, M., Chung, T.M. (eds) Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications. FDSE 2020. Communications in Computer and Information Science, vol 1306. Springer, Singapore. https://doi.org/10.1007/978-981-33-4370-2_21

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  • DOI: https://doi.org/10.1007/978-981-33-4370-2_21

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-33-4369-6

  • Online ISBN: 978-981-33-4370-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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