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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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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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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