First Steps of Asthma Management with a Personalized Ontology Model

Hicham Ajami, Hamid Mcheick and Catherine Laprise
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Hicham Ajami: Department of Computer Science and Mathematics, Université du Quebec à Chicoutimi, Chicoutimi, QC G7H 2B1, Canada
Hamid Mcheick: Department of Computer Science and Mathematics, Université du Quebec à Chicoutimi, Chicoutimi, QC G7H 2B1, Canada
Catherine Laprise: Fundamental Sciences Department, Université du Quebec à Chicoutimi, Chicoutimi, QC G7H 2B1, Canada

Future Internet, 2022, vol. 14, issue 7, 1-13

Abstract: Asthma is a chronic respiratory disease characterized by severe inflammation of the bronchial mucosa. Allergic asthma is the most common form of this health issue. Asthma is classified into allergic and non-allergic asthma, and it can be triggered by several factors such as indoor and outdoor allergens, air pollution, weather conditions, tobacco smoke, and food allergens, as well as other factors. Asthma symptoms differ in their frequency and severity since each patient reacts differently to these triggers. Formal knowledge is selected as one of the most promising solutions to deal with these challenges. This paper presents a new personalized approach to manage asthma. An ontology-driven model supported by Semantic Web Rule Language (SWRL) medical rules is proposed to provide personalized care for an asthma patient by identifying the risk factors and the development of possible exacerbations.

Keywords: asthma; SWRL; medical rules; pervasive computing; ontology model; architectural model; chronic respiratory disease; management systems (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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