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Preco Framework: A Predictive Approach for Comorbidities Risk Assessment

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Inclusive Smart Cities and e-Health (ICOST 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9102))

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Abstract

The overall objective of the PRECO framework is to investigate comorbidities’ patterns, based on the historic of comorbidities evolution, patient centric data and tele-health monitoring, for a predictive evaluation of comorbidity development risk and to determine the most probable one(s) the patient could declare.

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Authors and Affiliations

  1. Information Science Institute, Rte de Drize7, 1227, Carouge, Switzerland

    Mehdi Snene, Manel Sghir & Dimitri Konstantas

Authors
  1. Mehdi Snene
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  2. Manel Sghir
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  3. Dimitri Konstantas
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Corresponding authors

Correspondence to Mehdi Snene , Manel Sghir or Dimitri Konstantas .

Editor information

Editors and Affiliations

  1. University of Geneva, Geneva, Switzerland

    Antoine Geissbühler

  2. Université Joseph Fourier, Grenoble, France

    Jacques Demongeot

  3. Institut Mines Télécom Paris, CNRS IPAL (UMI 2955 Singapore), Paris, France

    Mounir Mokhtari

  4. Université de Sherbrooke, Sherbrooke, Québec, Canada

    Bessam Abdulrazak

  5. Institut Mines Télécom, CNRS LIRMM, Paris, France

    Hamdi Aloulou

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© 2015 Springer International Publishing Switzerland

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Snene, M., Sghir, M., Konstantas, D. (2015). Preco Framework: A Predictive Approach for Comorbidities Risk Assessment. In: Geissbühler, A., Demongeot, J., Mokhtari, M., Abdulrazak, B., Aloulou, H. (eds) Inclusive Smart Cities and e-Health. ICOST 2015. Lecture Notes in Computer Science(), vol 9102. Springer, Cham. https://doi.org/10.1007/978-3-319-19312-0_33

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  • DOI: https://doi.org/10.1007/978-3-319-19312-0_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19311-3

  • Online ISBN: 978-3-319-19312-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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