An Ontological Approach for Early Detection of Suspected COVID-19 among COPD Patients

Konan-Marcelin Kouamé,Hamid Mcheick

doi:10.3390/asi4010021

Abstract

Recent studies on chronic obstructive pulmonary disease (COPD) patients in the context of the coronavirus 19 (COVID-19) pandemic have reported two important problems, i.e., high mortality and vulnerability among COPD patients vs. non-COPD patients. The high number of deaths are caused by exacerbations, COVID-19, and other comorbidities. Therefore, the purpose of this article is to reduce the risk factors of COPD in the COVID-19 context. In this article, we propose approaches based on adaptation mechanisms for detecting COVID-19 symptoms, to better provide appropriate care to COPD patients. To achieve this goal, an ontological model called SuspectedCOPDcoviDOlogy has been created, which consists of five ontologies for detecting suspect cases. These ontologies use vital sign parameters, symptom parameters, service management, and alerts. SuspectedCOPDcoviDOlogy enhances the COPDology proposed by a previous research project in the COPD domain. To validate the solution, an experimental study comparing the results of an existing test for the detection of COVID-19 with the results of the proposed detection system is conducted. Finally, with these results, we conclude that a rigorous combination of detection rules based on the vital sign and symptom parameters can greatly improve the dynamic detection rate of COPD patients suspected of having COVID-19, and therefore enable rapid medical assistance.

Highlights

According to Sahoo et al [7], the implementation of telemedicine systems is necessary for the protection of chronic obstructive pulmonary disease (COPD) patients against COVID-19, “As COPD patients are at an increased risk of severe outcomes if they became infected with COVID-19, it is recommended that patients and clinicians establish effective plans for ensuring prevention, such as using tele-medicine to ensure that COPD receives the best care.”
COPD patients with COVID-19 model based on Ontology/OWL
Our solution (SuspectedCOPDcoviDOlogy) for detecting suspected cases enriches the knowledge of existing ontologies, such as COPDology in the field of COPD domain, for improving the quality of service of COPD patient monitoring platforms

Summary

Introduction

Since 2019, the world has been affected by the coronavirus 19 (COVID-19) or SARSCoV-2 (the name of the virus) pandemic, which has caused many deaths. All people are exposed, patients with chronic diseases remain the most vulnerable since they face a high risk of death. The mandatory social-distancing measures that have been implemented to combat the high infectiousness of the disease have increasingly encouraged the use of telemedicine. Telemedicine is used to assist patients from their homes or the hospital. These patients often suffer from breathing difficulties caused by chronic obstructive pulmonary disease (COPD)

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