AID-FGS: Artificial intelligence-enabled diagnosis of female genital schistosomiasis: Preliminary findings.

ABSTRACT: Female genital schistosomiasis (FGS) is a sequela of infection with a waterborne parasite prevalent in sub-Saharan Africa and is associated with increased HIV risk. Diagnosis of FGS involves visual colposcopic identification of lesions on the cervix or vaginal walls. Previous studies have utilized digital image processing methods with statistical validation, and more recently, an artificial intelligence (AI)-based approach has also been explored. In this work, we sought to evaluate the performance of an AI model for identifying the presence of FGS from cervical photographs. Colposcopy images were obtained from 340 subjects in Zambia. Ground truth for presence or absence of FGS was determined by trained expert human examiners using visual assessment of images. Examiners also provided a FGS

SUBMITTER: Sharma A 

PROVIDER: S-EPMC12923067 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature