Collaborative intelligence and gamification for on-line malaria species differentiation
Abstract Background Current World Health Organization recommendations for the management of malaria include the need for a parasitological confirmation prior to triggering appropriate treatment. The use of rapid diagnostic tests (RDTs) for malaria has contributed to a better infection recognition an...
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ftdoajarticles:oai:doaj.org/article:e8343c17ff1e4e1291bdc1ed727c1d87 2023-05-15T15:15:40+02:00 Collaborative intelligence and gamification for on-line malaria species differentiation María Linares María Postigo Daniel Cuadrado Alejandra Ortiz-Ruiz Sara Gil-Casanova Alexander Vladimirov Jaime García-Villena José María Nuñez-Escobedo Joaquín Martínez-López José Miguel Rubio María Jesús Ledesma-Carbayo Andrés Santos Quique Bassat Miguel Luengo-Oroz 2019-01-01T00:00:00Z https://doi.org/10.1186/s12936-019-2662-9 https://doaj.org/article/e8343c17ff1e4e1291bdc1ed727c1d87 EN eng BMC http://link.springer.com/article/10.1186/s12936-019-2662-9 https://doaj.org/toc/1475-2875 doi:10.1186/s12936-019-2662-9 1475-2875 https://doaj.org/article/e8343c17ff1e4e1291bdc1ed727c1d87 Malaria Journal, Vol 18, Iss 1, Pp 1-9 (2019) Crowdsourcing Malaria classification Image analysis Games for health Telepathology Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2019 ftdoajarticles https://doi.org/10.1186/s12936-019-2662-9 2022-12-31T09:17:50Z Abstract Background Current World Health Organization recommendations for the management of malaria include the need for a parasitological confirmation prior to triggering appropriate treatment. The use of rapid diagnostic tests (RDTs) for malaria has contributed to a better infection recognition and a more targeted treatment. Nevertheless, low-density infections and parasites that fail to produce HRP2 can cause false-negative RDT results. Microscopy has traditionally been the methodology most commonly used to quantify malaria and characterize the infecting species, but the wider use of this technique remains challenging, as it requires trained personnel and processing capacity. Objective In this study, the feasibility of an on-line system for remote malaria species identification and differentiation has been investigated by crowdsourcing the analysis of digitalized infected thin blood smears by non-expert observers using a mobile app. Methods An on-line videogame in which players learned how to differentiate the young trophozoite stage of the five Plasmodium species has been designed. Images were digitalized with a smartphone camera adapted to the ocular of a conventional light microscope. Images from infected red blood cells were cropped and puzzled into an on-line game. During the game, players had to decide the malaria species (Plasmodium falciparum, Plasmodium malariae, Plasmodium vivax, Plasmodium ovale, Plasmodium knowlesi) of the infected cells that were shown in the screen. After 2 months, each player’s decisions were analysed individually and collectively. Results On-line volunteers playing the game made more than 500,000 assessments for species differentiation. Statistically, when the choice of several players was combined (n > 25), they were able to significantly discriminate Plasmodium species, reaching a level of accuracy of 99% for all species combinations, except for P. knowlesi (80%). Non-expert decisions on which Plasmodium species was shown in the screen were made in less than 3 s. ... Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Malaria Journal 18 1 |
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Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
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English |
topic |
Crowdsourcing Malaria classification Image analysis Games for health Telepathology Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
spellingShingle |
Crowdsourcing Malaria classification Image analysis Games for health Telepathology Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 María Linares María Postigo Daniel Cuadrado Alejandra Ortiz-Ruiz Sara Gil-Casanova Alexander Vladimirov Jaime García-Villena José María Nuñez-Escobedo Joaquín Martínez-López José Miguel Rubio María Jesús Ledesma-Carbayo Andrés Santos Quique Bassat Miguel Luengo-Oroz Collaborative intelligence and gamification for on-line malaria species differentiation |
topic_facet |
Crowdsourcing Malaria classification Image analysis Games for health Telepathology Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
description |
Abstract Background Current World Health Organization recommendations for the management of malaria include the need for a parasitological confirmation prior to triggering appropriate treatment. The use of rapid diagnostic tests (RDTs) for malaria has contributed to a better infection recognition and a more targeted treatment. Nevertheless, low-density infections and parasites that fail to produce HRP2 can cause false-negative RDT results. Microscopy has traditionally been the methodology most commonly used to quantify malaria and characterize the infecting species, but the wider use of this technique remains challenging, as it requires trained personnel and processing capacity. Objective In this study, the feasibility of an on-line system for remote malaria species identification and differentiation has been investigated by crowdsourcing the analysis of digitalized infected thin blood smears by non-expert observers using a mobile app. Methods An on-line videogame in which players learned how to differentiate the young trophozoite stage of the five Plasmodium species has been designed. Images were digitalized with a smartphone camera adapted to the ocular of a conventional light microscope. Images from infected red blood cells were cropped and puzzled into an on-line game. During the game, players had to decide the malaria species (Plasmodium falciparum, Plasmodium malariae, Plasmodium vivax, Plasmodium ovale, Plasmodium knowlesi) of the infected cells that were shown in the screen. After 2 months, each player’s decisions were analysed individually and collectively. Results On-line volunteers playing the game made more than 500,000 assessments for species differentiation. Statistically, when the choice of several players was combined (n > 25), they were able to significantly discriminate Plasmodium species, reaching a level of accuracy of 99% for all species combinations, except for P. knowlesi (80%). Non-expert decisions on which Plasmodium species was shown in the screen were made in less than 3 s. ... |
format |
Article in Journal/Newspaper |
author |
María Linares María Postigo Daniel Cuadrado Alejandra Ortiz-Ruiz Sara Gil-Casanova Alexander Vladimirov Jaime García-Villena José María Nuñez-Escobedo Joaquín Martínez-López José Miguel Rubio María Jesús Ledesma-Carbayo Andrés Santos Quique Bassat Miguel Luengo-Oroz |
author_facet |
María Linares María Postigo Daniel Cuadrado Alejandra Ortiz-Ruiz Sara Gil-Casanova Alexander Vladimirov Jaime García-Villena José María Nuñez-Escobedo Joaquín Martínez-López José Miguel Rubio María Jesús Ledesma-Carbayo Andrés Santos Quique Bassat Miguel Luengo-Oroz |
author_sort |
María Linares |
title |
Collaborative intelligence and gamification for on-line malaria species differentiation |
title_short |
Collaborative intelligence and gamification for on-line malaria species differentiation |
title_full |
Collaborative intelligence and gamification for on-line malaria species differentiation |
title_fullStr |
Collaborative intelligence and gamification for on-line malaria species differentiation |
title_full_unstemmed |
Collaborative intelligence and gamification for on-line malaria species differentiation |
title_sort |
collaborative intelligence and gamification for on-line malaria species differentiation |
publisher |
BMC |
publishDate |
2019 |
url |
https://doi.org/10.1186/s12936-019-2662-9 https://doaj.org/article/e8343c17ff1e4e1291bdc1ed727c1d87 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Malaria Journal, Vol 18, Iss 1, Pp 1-9 (2019) |
op_relation |
http://link.springer.com/article/10.1186/s12936-019-2662-9 https://doaj.org/toc/1475-2875 doi:10.1186/s12936-019-2662-9 1475-2875 https://doaj.org/article/e8343c17ff1e4e1291bdc1ed727c1d87 |
op_doi |
https://doi.org/10.1186/s12936-019-2662-9 |
container_title |
Malaria Journal |
container_volume |
18 |
container_issue |
1 |
_version_ |
1766346017712635904 |