Sahmoud Shaaban

Deep learning–assisted malaria microscopy with sensitivity-aware threshold optimization

Malaria microscopy becomes clinically risky when parasitized erythrocytes are missed, even when a classifier reports high overall accuracy. This study presents an artificial-intelligence-assisted malaria microscopy framework that explicitly optimizes the diagnostic operating point for sensitivity-aware screening. A bal...