Remote analysis of sputum smears for mycobacterium tuberculosis quantification using digital crowdsourcing.
PLoS One
; 17(5): e0268494, 2022.
Article
em En
| MEDLINE
| ID: mdl-35587505
ABSTRACT
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.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Tuberculose dos Linfonodos
/
Tuberculose Pulmonar
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Crowdsourcing
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Mycobacterium tuberculosis
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article