RT Journal Article
T1 Remote analysis of sputum smears for mycobacterium tuberculosis quantification using digital crowdsourcing
A1 García Delgado, Lara
A1 Postigo, María
A1 Cuadrado, Daniel
A1 Gil-Casanova, Sara
A1 Martínez Martínez, Álvaro
A1 Linares Gómez, María
A1 Merino Amador, Paloma
A1 Gimo, Manuel
A1 Blanco, Silvia
A1 Bassat, Quique
A1 Santos, Andrés
A1 García-Basteiro, Alberto L.
A1 Ledesma-Carbayo, María J.
A1 Luengo-Oroz, Miguel Á.
A2 Frederick Quinn, 
AB 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.
SN 1932-6203
YR 2022
FD 2022-05-19
LK https://hdl.handle.net/20.500.14352/101967
UL https://hdl.handle.net/20.500.14352/101967
LA eng
NO Spanish Ministry of Science, Innovation and Universities
NO Spotlab
NO Comunidad de Madrid
NO Government of Mozambique
NO Spanish Agency for International Development
DS Docta Complutense
RD 14 dic 2025