Remote microscopy diagnostics (ReMiDi) with machine learning in malaria parasite detection
The rapid diagnosis of malaria, where microscopy is the gold standard for detection, is critical for its effective treatment. However, microscopy-based diagnostics heavily rely on the availability of trained technicians, especially in remote locations. The automation of microscopy diagnostics can he...
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| Formato: | Thesis |
| Idioma: | English |
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