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
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, fully- or semi-integrat...
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| Hauptverfasser: | , , , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
28 June 2024
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| In: |
Malaria journal
Year: 2024, Jahrgang: 23, Pages: 1-9 |
| ISSN: | 1475-2875 |
| DOI: | 10.1186/s12936-024-05029-3 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1186/s12936-024-05029-3
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| Verfasserangaben: | 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 and Seda Yerlikaya |
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| 520 | |a 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, fully- or semi-integrated microscopes that can improve slide preparation and examination. This study aimed to evaluate the clinical performance of miLab™ (Noul Inc., Republic of Korea), a fully-integrated automated microscopy device for the detection of malaria parasites in symptomatic patients at point-of-care in Sudan. | ||
| 650 | 4 | |a Artificial intelligence | |
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