Evaluating the performance of an artificial intelligence-based electronic reader for malaria rapid diagnostic tests across Benin, Côte d’Ivoire, Nigeria and Uganda

Background The introduction of malaria rapid diagnostic tests (RDTs) has expanded the parasitological confirmation of malaria at all levels of health systems in sub-Saharan Africa, improving case management and surveillance. However, concerns persist regarding healthcare worker adherence to RDT outc...

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Vydané v:	Malaria journal Ročník 24; číslo 1; s. 302 - 12
Hlavní autori:	Lindblade, Kim A., Ngufor, Corine, Yavo, William, Atobatele, Sunday, Mpimbaza, Arthur, Ssewante, Nelson, Akpiroroh, Ese, Konaté-Toure, Abibatou, Ahogni, Idelphonse, Kpemasse, Augustin, Tanoh, Antoine Mea, Ntadom, Godwin, Opigo, Jimmy, Zobrist, Stephanie, Griffith, Kevin, Humes, Michael
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London BioMed Central 30.09.2025 BioMed Central Ltd BMC
Predmet:	Adult Artificial Intelligence Benin Biomedical and Life Sciences Biomedicine Computer-aided medical diagnosis Cote d'Ivoire Diagnosing the Data: Malaria RDT Recording and Reporting Accuracy in Four African Countries and Implications for Surveillance Diagnosis Diagnostic accuracy Diagnostic Tests, Routine - instrumentation Diagnostic Tests, Routine - methods Digital health Electronic RDT reader Entomology Female Humans Infectious Diseases Malaria Malaria - diagnosis Male Methods Microbiology Molecular diagnostic techniques Nigeria Parasitology Public Health Rapid diagnostic test Rapid Diagnostic Tests Sensitivity and Specificity Tropical Medicine Uganda Benin Uganda Nigeria Cote d'Ivoire Sub-Saharan Africa Rapid diagnostic test Digital health Malaria Artificial intelligence Diagnostic accuracy Electronic RDT reader
ISSN:	1475-2875, 1475-2875
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