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Intelligent Diagnosis and Treatment Research of Knee Osteoarthritis Based on Big Data

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Smart Health (ICSH 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10983))

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Abstract

Knee Osteoarthritis (KOA) is a common and frequently-occurring chronic disease. The traditional KOA diagnosis lacks personalized and systematic diagnosis and treatment models, and lacks high-quality and large-sample randomized controlled clinical studies. In this paper, we propose a kind of intelligent diagnosis and treatment method for KOA based on big data and artificial intelligence.

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Acknowledgment

This work was supported by NSFC (91646202), Research/Project 2017YB142 supported by Ministry of Education of The People’s Republic of China, the 1000-Talent program.

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Authors and Affiliations

  1. Department of Rehabilitation, Beijing Tsinghua Changgung Hospital, Beijing, 100084, China

    Xin Li

  2. Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Guigang Zhang

  3. Research Institute of Information Technology, Beijing, China

    Chunxiao Xing & Yong Zhang

  4. Beijing National Research Center for Information Science and Technology, Beijing, China

    Chunxiao Xing & Yong Zhang

  5. Department of Computer Science and Technology, Beijing, China

    Chunxiao Xing & Yong Zhang

  6. Institute of Internet Industry, Tsinghua University, Beijing, 100084, China

    Chunxiao Xing & Yong Zhang

Authors
  1. Xin Li
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  2. Guigang Zhang
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  3. Chunxiao Xing
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  4. Yong Zhang
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Corresponding author

Correspondence to Xin Li .

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Editors and Affiliations

  1. University of Arizona, Tucson, AZ, USA

    Hsinchun Chen

  2. Wuhan University, Wuhan, China

    Qing Fang

  3. University of Arizona, Tucson, AZ, USA

    Daniel Zeng

  4. Wuhan University, Wuhan, China

    Jiang Wu

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Li, X., Zhang, G., Xing, C., Zhang, Y. (2018). Intelligent Diagnosis and Treatment Research of Knee Osteoarthritis Based on Big Data. In: Chen, H., Fang, Q., Zeng, D., Wu, J. (eds) Smart Health. ICSH 2018. Lecture Notes in Computer Science(), vol 10983. Springer, Cham. https://doi.org/10.1007/978-3-030-03649-2_18

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  • DOI: https://doi.org/10.1007/978-3-030-03649-2_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03648-5

  • Online ISBN: 978-3-030-03649-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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