Field evaluation of the diagnostic performance of EasyScan GO: a digital malaria microscopy device based on machine-learning

Background: Microscopic examination of Giemsa-stained blood films remains the reference standard for malaria parasite detection and quantification, but is undermined by difficulties in ensuring high-quality manual reading and inter-reader reliability. Automated parasite detection and quantification...

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Bibliographic Details
Main Author: Das D.
Other Authors: Mahidol University
Format: Article
Published: 2023
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Online Access:https://repository.li.mahidol.ac.th/handle/123456789/84861
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Institution: Mahidol University

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