Accuracy of AI-assisted diagnostic tools for Schistosoma haematobium: A systematic review and meta-analysis
by Sisay Desale, Getaneh Alemu, Tadesse Hailu
BackgroundUrogenital schistosomiasis caused by Schistosoma haematobium remains endemic in sub-Saharan Africa. Diagnosis traditionally relies on urine microscopy to detect parasite eggs; however, its sensitivity declines in low-intensity infections. Artificial intelligence (AI)-assisted image analysis offers a promising approach to automate egg detection and enhance diagnostic accuracy, but its performance compared with standard microscopy is not well established. Читать дальше...