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...
Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
BioMed Central Ltd
2022
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Subjects: | |
Online Access: | View Fulltext in Publisher |