Application of artificial intelligence for quantifying Plasmodium berghei in blood samples of infected mice

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dc.contributor.authorZelai, Noha Talalen_US
dc.date.accessioned2025-08-13T09:35:51Z
dc.date.available2025-08-13T09:35:51Z
dc.date.issued2025-06
dc.description.abstractBackground & objectives: In malaria infection, quantifying blood parasitemia is a critical step for evaluating the severity of the disease. This has generally been conducted manually, and thus its accuracy depends on technician expertise. There is an urgent need for an automated technique to overcome manual errors. The aim of this study was to find an alternative method for counting malaria blood parasitemia. Methods: This study evaluated the accuracy of automated counting using QuPath compared to manual counting. GraphPad Kappa evaluated agreement between high and low parasitemia in both counting methods using Cohen’s test. Results: QuPath was revealed to be a promising method that has fair agreement and no statistically significant differences compared to manual counting. Interpretation & conclusion: Automated quantification is suggested to be a time and effort-saving technique and therefore is a worthwhile alternative to manual counting.en_US
dc.identifier.affiliationsDepartment of Biological Sciences, King Abdul Aziz University, Jeddah, Makkah, Saudi Arabiaen_US
dc.identifier.citationZelai Noha Talal. Application of artificial intelligence for quantifying Plasmodium berghei in blood samples of infected mice. Journal of Vector Borne Diseases . 2025 Jun; 62(2): 233-236en_US
dc.identifier.issn0972-9062
dc.identifier.placeIndiaen_US
dc.identifier.urihttps://imsear.searo.who.int/handle/123456789/252559
dc.languageenen_US
dc.publisherWolters Kluwer – Medknowen_US
dc.relation.issuenumber2en_US
dc.relation.volume62en_US
dc.source.urihttps://doi.org/10.4103/JVBD.JVBD_86_24https://creativecommons.org/licenses/by-nc-sa/4.0en_US
dc.subjectMalariaen_US
dc.subjectquantifyingen_US
dc.subjectparasitemiaen_US
dc.subjectautomateden_US
dc.subjectmanualen_US
dc.titleApplication of artificial intelligence for quantifying Plasmodium berghei in blood samples of infected miceen_US
dc.typeJournal Articleen_US
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