%0 Journal Article
%A García Delgado, Lara
%A Postigo, María
%A Cuadrado, Daniel
%A Gil-Casanova, Sara
%A Martínez Martínez, Álvaro
%A Linares Gómez, María
%A Merino Amador, Paloma
%A Gimo, Manuel
%A Blanco, Silvia
%A Bassat, Quique
%A Santos, Andrés
%A García-Basteiro, Alberto L.
%A Ledesma-Carbayo, María J.
%A Luengo-Oroz, Miguel Á.
%T Remote analysis of sputum smears for mycobacterium tuberculosis quantification using digital crowdsourcing
%D 2022
%@ 1932-6203
%U https://hdl.handle.net/20.500.14352/101967
%X Worldwide, TB is one of the top 10 causes of death and the leading cause from a single infectious agent. Although the development and roll out of Xpert MTB/RIF has recently become a major breakthrough in the field of TB diagnosis, smear microscopy remains the most widely used method for TB diagnosis, especially in low- and middle-income countries. This research tests the feasibility of a crowdsourced approach to tuberculosis image analysis. In particular, we investigated whether anonymous volunteers with no prior experience would be able to count acid-fast bacilli in digitized images of sputum smears by playing an online game. Following this approach 1790 people identified the acid-fast bacilli present in 60 digitized images, the best overall performance was obtained with a specific number of combined analysis from different players and the performance was evaluated with the F1 score, sensitivity and positive predictive value, reaching values of 0.933, 0.968 and 0.91, respectively.
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