A Virtual Reading Center Model Using Crowdsourcing to Grade Photographs for Trachoma: Validation Study.

Christopher John Brady Robert Chase Cockrell Lindsay R Aldrich Meraf A Wolle Sheila K West

Published in: Journal of medical Internet research (2023)

A VRC model using crowdsourcing as a first pass with skilled grading of positive images was able to identify TF rapidly and accurately in a low prevalence setting. The findings from this study support further validation of a VRC and crowdsourcing for image grading and estimation of trachoma prevalence from field-acquired images, although further prospective field testing is required to determine if diagnostic characteristics are acceptable in real-world surveys with a low prevalence of the disease.

Keyphrases

deep learning
risk factors
convolutional neural network
cross sectional