Diagnostic accuracy of an automated microscope solution (miLab™) in detecting malaria parasites in symptomatic patients at point-of-care in Sudan: a case–control study

Diagnostic accuracy of an automated microscope solution (miLab™) in detecting malaria parasites in symptomatic patients at point-of-care in Sudan: a case–control study

Abstract Background Microscopic detection of malaria parasites is labour-intensive, time-consuming, and expertise-demanding. Moreover, the slide interpretation is highly dependent on the staining technique and the technician’s expertise. Therefore, there is a growing interest in next-generation, ful...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy: Muzamil M. Abdel Hamid, Abdelrahim O. Mohamed, Fayad O. Mohammed, Arwa Elaagip, Sayed A. Mustafa, Tarig Elfaki, Waleed M. A. Jebreel, Musab M. Albsheer, Sabine Dittrich, Ewurama D. A. Owusu, Seda Yerlikaya
Format: Artykuł
Język:English
Wydane: BMC 2024-06-01
Seria:Malaria Journal
Hasła przedmiotowe:
Automated microscope
Artificial intelligence
miLab™
Malaria
Sudan
Dostęp online:https://doi.org/10.1186/s12936-024-05029-3

Internet

https://doi.org/10.1186/s12936-024-05029-3

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