Evaluation of an Artificial Intelligence-Based Tool and a Universal Low-Cost Robotized Microscope for the Automated Diagnosis of Malaria

The gold standard diagnosis for malaria is the microscopic visualization of blood smears to identify Plasmodium parasites, although it is an expert-dependent technique and could trigger diagnostic errors. Artificial intelligence (AI) tools based on digital image analysis were postulated as a suitabl...

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Autores: Rubio Maturana, Carles, Dantas de Oliveira, Allisson|||0000-0002-8267-9760, Serrat, Francesc Zarzuela|||0000-0001-7520-978X, Mediavilla, Alejandro, Martínez-Vallejo, Patricia, Silgado, Aroa|||0000-0001-7581-0049, Goterris, Lidia|||0000-0003-1471-4461, Muixí, Marc, Abelló, Alberto|||0000-0002-3223-2186, Veiga, Anna|||0000-0002-0943-9904, López i Codina, Daniel|||0000-0002-0408-4526, Sulleiro, Elena|||0000-0002-9783-6060, Sayrol, Elisa|||0000-0002-0526-9733, Joseph-Munné, Joan
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:307843
Acceso en línea:https://ddd.uab.cat/record/307843
https://dx.doi.org/urn:doi:10.3390/ijerph22010047
Access Level:acceso abierto
Palabra clave:Artificial intelligence
Malaria
Automated diagnosis
Tropical medicine
Plasmodium
Point-of-care
Infectious diseases
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spelling Evaluation of an Artificial Intelligence-Based Tool and a Universal Low-Cost Robotized Microscope for the Automated Diagnosis of MalariaRubio Maturana, CarlesDantas de Oliveira, Allisson|||0000-0002-8267-9760Serrat, Francesc Zarzuela|||0000-0001-7520-978XMediavilla, AlejandroMartínez-Vallejo, PatriciaSilgado, Aroa|||0000-0001-7581-0049Goterris, Lidia|||0000-0003-1471-4461Muixí, MarcAbelló, Alberto|||0000-0002-3223-2186Veiga, Anna|||0000-0002-0943-9904López i Codina, Daniel|||0000-0002-0408-4526Sulleiro, Elena|||0000-0002-9783-6060Sayrol, Elisa|||0000-0002-0526-9733Joseph-Munné, JoanArtificial intelligenceMalariaAutomated diagnosisTropical medicinePlasmodiumPoint-of-careInfectious diseasesThe gold standard diagnosis for malaria is the microscopic visualization of blood smears to identify Plasmodium parasites, although it is an expert-dependent technique and could trigger diagnostic errors. Artificial intelligence (AI) tools based on digital image analysis were postulated as a suitable supportive alternative for automated malaria diagnosis. A diagnostic evaluation of the iMAGING AI-based system was conducted in the reference laboratory of the International Health Unit Drassanes-Vall d'Hebron in Barcelona, Spain. iMAGING is an automated device for the diagnosis of malaria by using artificial intelligence image analysis tools and a robotized microscope. A total of 54 Giemsa-stained thick blood smear samples from travelers and migrants coming from endemic areas were employed and analyzed to determine the presence/absence of Plasmodium parasites. AI diagnostic results were compared with expert light microscopy gold standard method results. The AI system shows 81.25% sensitivity and 92.11% specificity when compared with the conventional light microscopy gold standard method. Overall, 48/54 (88.89%) samples were correctly identified [13/16 (81.25%) as positives and 35/38 (92.11%) as negatives]. The mean time of the AI system to determine a positive malaria diagnosis was 3 min and 48 s, with an average of 7.38 FoV analyzed per sample. Statistical analyses showed the Kappa Index = 0.721, demonstrating a satisfactory correlation between the gold standard diagnostic method and iMAGING results. The AI system demonstrated reliable results for malaria diagnosis in a reference laboratory in Barcelona. Validation in malaria-endemic regions will be the next step to evaluate its potential in resource-poor settings. 22025-01-0120252025-01-01Articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://ddd.uab.cat/record/307843https://dx.doi.org/urn:doi:10.3390/ijerph22010047reponame:Dipòsit Digital de Documents de la UABinstname:Universitat Autònoma de BarcelonaInglésengopen accesshttp://purl.org/coar/access_right/c_abf2Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:ddd.uab.cat:3078432026-06-06T12:50:31Z
dc.title.none.fl_str_mv Evaluation of an Artificial Intelligence-Based Tool and a Universal Low-Cost Robotized Microscope for the Automated Diagnosis of Malaria
title Evaluation of an Artificial Intelligence-Based Tool and a Universal Low-Cost Robotized Microscope for the Automated Diagnosis of Malaria
spellingShingle Evaluation of an Artificial Intelligence-Based Tool and a Universal Low-Cost Robotized Microscope for the Automated Diagnosis of Malaria
Rubio Maturana, Carles
Artificial intelligence
Malaria
Automated diagnosis
Tropical medicine
Plasmodium
Point-of-care
Infectious diseases
title_short Evaluation of an Artificial Intelligence-Based Tool and a Universal Low-Cost Robotized Microscope for the Automated Diagnosis of Malaria
title_full Evaluation of an Artificial Intelligence-Based Tool and a Universal Low-Cost Robotized Microscope for the Automated Diagnosis of Malaria
title_fullStr Evaluation of an Artificial Intelligence-Based Tool and a Universal Low-Cost Robotized Microscope for the Automated Diagnosis of Malaria
title_full_unstemmed Evaluation of an Artificial Intelligence-Based Tool and a Universal Low-Cost Robotized Microscope for the Automated Diagnosis of Malaria
title_sort Evaluation of an Artificial Intelligence-Based Tool and a Universal Low-Cost Robotized Microscope for the Automated Diagnosis of Malaria
dc.creator.none.fl_str_mv Rubio Maturana, Carles
Dantas de Oliveira, Allisson|||0000-0002-8267-9760
Serrat, Francesc Zarzuela|||0000-0001-7520-978X
Mediavilla, Alejandro
Martínez-Vallejo, Patricia
Silgado, Aroa|||0000-0001-7581-0049
Goterris, Lidia|||0000-0003-1471-4461
Muixí, Marc
Abelló, Alberto|||0000-0002-3223-2186
Veiga, Anna|||0000-0002-0943-9904
López i Codina, Daniel|||0000-0002-0408-4526
Sulleiro, Elena|||0000-0002-9783-6060
Sayrol, Elisa|||0000-0002-0526-9733
Joseph-Munné, Joan
author Rubio Maturana, Carles
author_facet Rubio Maturana, Carles
Dantas de Oliveira, Allisson|||0000-0002-8267-9760
Serrat, Francesc Zarzuela|||0000-0001-7520-978X
Mediavilla, Alejandro
Martínez-Vallejo, Patricia
Silgado, Aroa|||0000-0001-7581-0049
Goterris, Lidia|||0000-0003-1471-4461
Muixí, Marc
Abelló, Alberto|||0000-0002-3223-2186
Veiga, Anna|||0000-0002-0943-9904
López i Codina, Daniel|||0000-0002-0408-4526
Sulleiro, Elena|||0000-0002-9783-6060
Sayrol, Elisa|||0000-0002-0526-9733
Joseph-Munné, Joan
author_role author
author2 Dantas de Oliveira, Allisson|||0000-0002-8267-9760
Serrat, Francesc Zarzuela|||0000-0001-7520-978X
Mediavilla, Alejandro
Martínez-Vallejo, Patricia
Silgado, Aroa|||0000-0001-7581-0049
Goterris, Lidia|||0000-0003-1471-4461
Muixí, Marc
Abelló, Alberto|||0000-0002-3223-2186
Veiga, Anna|||0000-0002-0943-9904
López i Codina, Daniel|||0000-0002-0408-4526
Sulleiro, Elena|||0000-0002-9783-6060
Sayrol, Elisa|||0000-0002-0526-9733
Joseph-Munné, Joan
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Artificial intelligence
Malaria
Automated diagnosis
Tropical medicine
Plasmodium
Point-of-care
Infectious diseases
topic Artificial intelligence
Malaria
Automated diagnosis
Tropical medicine
Plasmodium
Point-of-care
Infectious diseases
description The gold standard diagnosis for malaria is the microscopic visualization of blood smears to identify Plasmodium parasites, although it is an expert-dependent technique and could trigger diagnostic errors. Artificial intelligence (AI) tools based on digital image analysis were postulated as a suitable supportive alternative for automated malaria diagnosis. A diagnostic evaluation of the iMAGING AI-based system was conducted in the reference laboratory of the International Health Unit Drassanes-Vall d'Hebron in Barcelona, Spain. iMAGING is an automated device for the diagnosis of malaria by using artificial intelligence image analysis tools and a robotized microscope. A total of 54 Giemsa-stained thick blood smear samples from travelers and migrants coming from endemic areas were employed and analyzed to determine the presence/absence of Plasmodium parasites. AI diagnostic results were compared with expert light microscopy gold standard method results. The AI system shows 81.25% sensitivity and 92.11% specificity when compared with the conventional light microscopy gold standard method. Overall, 48/54 (88.89%) samples were correctly identified [13/16 (81.25%) as positives and 35/38 (92.11%) as negatives]. The mean time of the AI system to determine a positive malaria diagnosis was 3 min and 48 s, with an average of 7.38 FoV analyzed per sample. Statistical analyses showed the Kappa Index = 0.721, demonstrating a satisfactory correlation between the gold standard diagnostic method and iMAGING results. The AI system demonstrated reliable results for malaria diagnosis in a reference laboratory in Barcelona. Validation in malaria-endemic regions will be the next step to evaluate its potential in resource-poor settings.
publishDate 2025
dc.date.none.fl_str_mv 2
2025-01-01
2025
2025-01-01
dc.type.none.fl_str_mv Article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://ddd.uab.cat/record/307843
https://dx.doi.org/urn:doi:10.3390/ijerph22010047
url https://ddd.uab.cat/record/307843
https://dx.doi.org/urn:doi:10.3390/ijerph22010047
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Dipòsit Digital de Documents de la UAB
instname:Universitat Autònoma de Barcelona
instname_str Universitat Autònoma de Barcelona
reponame_str Dipòsit Digital de Documents de la UAB
collection Dipòsit Digital de Documents de la UAB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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