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Case-Based Reasoning for Context-Aware Solutions Supporting Personalised Asthma Management

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Artificial Intelligence and Soft Computing (ICAISC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11509))

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Abstract

Context-aware solutions have the potential to address the personalisation required for implementing asthma management plans. However, they have limitations to aid people with asthma when their triggers and symptoms are poorly known or changing. Case-Based Reasoning can address these limitations as it can effectively deal with personal constraints in problems that involve evolving context adaptation. This research work proposes to use Case-Based Reasoning together with Context-Aware Reasoning to aid the personalisation of asthma management plans at specific stages of the condition when the triggers and symptoms are not completely known or evolving. The proposal was implemented and evaluated using historical weather and air pollution data, and two control cases that were defined based on a set of interviews. Finally, the benefits and challenges of the proposal are presented and analysed based on the results of the evaluation.

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Notes

  1. 1.

    https://www.worldweatheronline.com/developer/api/.

  2. 2.

    https://www.londonair.org.uk/Londonair/API/.

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Acknowledgement

We thank Asthma UK for spreading the questionnaire (Sect. 3), among their representative network of people with asthma and carers. The link to the questionnaire is https://figshare.com/s/9f6b5e8a677ebd223f4a. The Context and Context-awareness definitions in Sect. 1 were provided by J.C. Augusto.

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Authors and Affiliations

  1. Research Group on Development of Intelligent Environments, Middlesex University, London, UK

    Mario Quinde, Nawaz Khan & Juan Carlos Augusto

  2. University of Piura, Piura, Peru

    Mario Quinde

Authors
  1. Mario Quinde
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  2. Nawaz Khan
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  3. Juan Carlos Augusto
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Corresponding author

Correspondence to Mario Quinde .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Quinde, M., Khan, N., Augusto, J.C. (2019). Case-Based Reasoning for Context-Aware Solutions Supporting Personalised Asthma Management. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2019. Lecture Notes in Computer Science(), vol 11509. Springer, Cham. https://doi.org/10.1007/978-3-030-20915-5_24

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  • DOI: https://doi.org/10.1007/978-3-030-20915-5_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20914-8

  • Online ISBN: 978-3-030-20915-5

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