Geodesic
Probabilistic Reasoning for Diagnosis Prediction of Coronavirus Disease based on Probabilistic Ontology
Computer Science and Information Systems, Tome 20 (2023) no. 3.

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The novel Coronavirus has been declared a pandemic by the World Health Organization (WHO). Predicting the diagnosis of COVID-19 is essential for disease cure and control. The paper’s main aim is to predict the COVID-19 diagnosis using probabilistic ontologies to address the randomness and incompleteness of knowledge. Our approach begins with constructing the entities, attributes, and relationships of COVID-19 ontology, by extracting symptoms and risk factors. The probabilistic components of COVID-19 ontology are developed by creating a Multi-Entity Bayesian Network, then determining its components, with the different nodes, as probability distribution linked to various nodes. We use probabilistic inference for predicting COVID-19 diagnosis, using the Situation-Specific Bayesian Network (SSBN). To validate the solution, an experimental study is conducted on real cases, comparing the results of existing machine learning methods, our solution presents an encouraging result and, therefore enables fast medical assistance.
Keywords: COVID-19, Probabilistic Ontology, Multi-Entity Bayesian Networks, Uncertainty, Reasoning 
@article{CSIS_2023_20_3_a12,
     author = {Messaouda Fareh and Ishak Riali and Hafsa Kherbache and Marwa Guemmouz},
     title = {Probabilistic {Reasoning} for {Diagnosis} {Prediction} of {Coronavirus} {Disease} based on {Probabilistic} {Ontology}},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {20},
     number = {3},
     year = {2023},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2023_20_3_a12/}
}
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Messaouda Fareh; Ishak Riali; Hafsa Kherbache; Marwa Guemmouz. Probabilistic Reasoning for Diagnosis Prediction of Coronavirus Disease based on Probabilistic Ontology. Computer Science and Information Systems, Tome 20 (2023) no. 3. http://geodesic.mathdoc.fr/item/CSIS_2023_20_3_a12/