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International Conference on Intelligent Computing

ICIC 2010: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence pp 91–99Cite as

PCOPM: A Probabilistic CBR Framework for Obesity Prescription Management

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6216))

Abstract

Obesity has become one of the most prevalent health problems around the world. Many obesity therapy cases need efficient management in order to be shared and utilized. Prescription management has been proved to be successful strategy in obesity management. Since a case usually contains incomplete information, this article examines probabilistic case-based reasoning (CBR) by integrating Bayesian networks (BN) with CBR and proposes a probabilistic CBR framework for obesity prescription management (PCOPM) to assist health professionals to share their experiences of obesity exercise prescription online. The PCOPM ties together CBR and BN into a unified framework that includes both obesity experience and intelligent embodiment of decision making for obesity management. The proposed approach will facilitate the research and development of intelligent web-based obesity management.

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Author information

Authors and Affiliations

  1. College of Mathematics and Information Science, Hebei Normal University, Shijiazhuang, 050016, China

    Dong Dong

  2. College of Physical Education, Hebei Normal University, Shijiazhuang, 050016, China

    Feng Gao

  3. Graduate School of Information Technology and Mathematical Sciences, University Of Ballarat, Ballarat, Victoria, 3353, Australia

    Zhaohao Sun

Authors
  1. Dong Dong
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  2. Zhaohao Sun
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  3. Feng Gao
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Editor information

Editors and Affiliations

  1. Chinese Academy of Sciences, Intelligent Computing Laboratory, P.O. Box 1130, 230031, Hefei, Anhui, China

    De-Shuang Huang

  2. Department of Chemistry, University of Louisville, 2320 South Brook Street, 40292, Louisville, KY, USA

    Xiang Zhang

  3. Department of Computational Sciences, National Institute of Astrophysics Optics and Electronics, Luis E. Erro #1, 72840, Tonantzintla, Puebla, Mexico

    Carlos Alberto Reyes García

  4. Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China

    Lei Zhang

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© 2010 Springer-Verlag Berlin Heidelberg

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Dong, D., Sun, Z., Gao, F. (2010). PCOPM: A Probabilistic CBR Framework for Obesity Prescription Management. In: Huang, DS., Zhang, X., Reyes García, C.A., Zhang, L. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2010. Lecture Notes in Computer Science(), vol 6216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14932-0_12

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  • DOI: https://doi.org/10.1007/978-3-642-14932-0_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14931-3

  • Online ISBN: 978-3-642-14932-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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