Case-based reasoning for context-aware solutions supporting personalised asthma management

Quinde, Mario, Khan, Nawaz and Augusto, Juan Carlos (2019) Case-based reasoning for context-aware solutions supporting personalised asthma management. In: 18th International Conference on Artificial Intelligence and Soft Computing (ICAISC 2019), 16-20 Jun 2019, Zakopane, Poland.

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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.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Paper published as: 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
Research Areas: A. > School of Science and Technology > Computer Science > Artificial Intelligence group
Item ID: 26576
Notes on copyright: The final authenticated version is available online at https://doi.org/10.1007/978-3-030-20915-5_24
Useful Links:
Depositing User: Nawaz Khan
Date Deposited: 13 May 2019 10:21
Last Modified: 10 Jun 2019 16:24
URI: https://eprints.mdx.ac.uk/id/eprint/26576

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