Performance of a fully‐automated system on a WHO malaria microscopy evaluation slide set

BACKGROUND: Manual microscopy remains a widely-used tool for malaria diagnosis and clinical studies, but it has inconsistent quality in the field due to variability in training and field practices. Automated diagnostic systems based on machine learning hold promise to improve quality and reproducibi...

Descrición completa

Gardado en:
Detalles Bibliográficos
Publicado en:Malar J
Main Authors: Horning, Matthew P., Delahunt, Charles B., Bachman, Christine M., Luchavez, Jennifer, Luna, Christian, Hu, Liming, Jaiswal, Mayoore S., Thompson, Clay M., Kulhare, Sourabh, Janko, Samantha, Wilson, Benjamin K., Ostbye, Travis, Mehanian, Martha, Gebrehiwot, Roman, Yun, Grace, Bell, David, Proux, Stephane, Carter, Jane Y., Oyibo, Wellington, Gamboa, Dionicia, Dhorda, Mehul, Vongpromek, Ranitha, Chiodini, Peter L., Ogutu, Bernhards, Long, Earl G., Tun, Kyaw, Burkot, Thomas R., Lilley, Ken, Mehanian, Courosh
Formato: Artigo
Idioma:Inglês
Publicado: BioMed Central 2021
Assuntos:
Research
Acceso en liña:https://ncbi.nlm.nih.gov/pmc/articles/PMC7905596/
https://ncbi.nlm.nih.gov/pubmed/33632222
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12936-021-03631-3
Tags: Engadir etiqueta
Sen Etiquetas, Sexa o primeiro en etiquetar este rexistro!

Títulos similares