AIMC Topic: Trachoma

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Computer Vision Identification of Trachomatous Inflammation-Follicular Using Deep Learning.

Cornea Sep 20, 2024
PURPOSE: Trachoma surveys are used to estimate the prevalence of trachomatous inflammation-follicular (TF) to guide mass antibiotic distribution. These surveys currently rely on human graders, introducing a significant resource burden and potential f...
Humans Neural Networks, Computer Female Infant, Newborn Reproducibility of Results Sensitivity and Specificity Male Infant Prevalence Diagnosis, Computer-Assisted Deep Learning Child, Preschool Child ROC Curve Ethiopia Conjunctiva Photography Eyelids Trachoma
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Sensitivity and specificity of computer vision classification of eyelid photographs for programmatic trachoma assessment.

PloS one Feb 11, 2019
BACKGROUND/AIMS: Trachoma programs base treatment decisions on the community prevalence of the clinical signs of trachoma, assessed by direct examination of the conjunctiva. Automated assessment could be more standardized and more cost-effective. We ...
Humans Neural Networks, Computer Artificial Intelligence Algorithms Prevalence Image Processing, Computer-Assisted Ethiopia Conjunctiva Photography Eyelids Niger Trachoma
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