HMC-COVID-19: Hidden Markov Chains Model for COVID-19 Diagnosis

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dc.contributor.authorGoumiri, Soumia
dc.contributor.authorBenboudjema, Dalila
dc.date.accessioned2024-01-29T09:37:37Z
dc.date.available2024-01-29T09:37:37Z
dc.date.issued2023
dc.description.abstractMarkov chains are probabilistic models that are useful in different image processing tasks. This paper presents an approach based on Hidden Markov Chain (HMCs) to diagnose COVID-19, that we named HMC-COVID-19. To assess the performance of the proposed solution, we use a public dataset of chest X-RAY images. Our solution has been evaluated using the accuracy of prediction. The preliminary results are promising and can be further enhanced.
dc.identifier.doi10.1109/DASA59624.2023.10286601
dc.identifier.isbn979-8-3503-4206-2
dc.identifier.isbn979-8-3503-4205-5
dc.identifier.urihttps://dl.cerist.dz/handle/CERIST/1006
dc.publisherIEEE
dc.relation.ispartofseriesDASA’23 International Conference on Decision Aid Sciences and Applications, 16-17 Sept. 2023
dc.relation.pages500-504
dc.relation.placeAnnaba, Algeria
dc.structureCalcul pervasif et mobile (Pervasive and Mobile Computing group)
dc.subjectHidden Markov Chains (HMC)
dc.subjectCOVID-19 diagnosis
dc.subjectHMC-COVID-19
dc.subjectImage classification
dc.titleHMC-COVID-19: Hidden Markov Chains Model for COVID-19 Diagnosis
dc.typeConference paper
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