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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Main Author: | Das D. |
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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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