IMA Fungus 15(1): e34114, doi: 10.1186/s43008-024-00158-5
Artificial intelligence-driven mobile interpretation of a semi-quantitative cryptococcal antigen lateral flow assay
David Bermejo-Peláez‡, Ana Alastruey-Izquierdo§, Narda Medina|, Daniel Capellán-Martín‡, Oscar Bonilla§, Miguel Luengo-Oroz‡, Juan Luis Rodríguez-Tudela¶‡ Spotlab, Madrid, Spain§ Instituto de Salud Carlos III, Mycology Reference Laboratory, National Center for Microbiology, Madrid, Spain| Asociación de Salud Integral, Guatemala City, Guatemala¶ Global Action for Fungal Infections, Geneva, Switzerland
© David Bermejo-Peláez, Ana Alastruey-Izquierdo, Narda Medina, Daniel Capellán-Martín, Oscar Bonilla, Miguel Luengo-Oroz, Juan Rodríguez-Tudela. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY-NC 4.0), which permits to copy and distribute the article for non-commercial purposes, provided that the article is not altered or modified and the original author and source are credited. Citation:
Bermejo-Peláez D, Alastruey-Izquierdo A, Medina N, Capellán-Martín D, Bonilla O, Luengo-Oroz M, Rodríguez-Tudela J (2024) Artificial intelligence-driven mobile interpretation of a semi-quantitative cryptococcal antigen lateral flow assay. IMA Fungus 15(1): e34114. https://doi.org/10.1186/s43008-024-00158-5 |  |
Keywords
Cryptococcosis, Lateral flow assay (LFA), Artificial intelligence (AI), Smartphone, Semiquantitative assay, Antigen quantification