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Automated detection and staging of malaria parasites from cytological smears using convolutional neural networks
Microscopic examination of blood smears remains the gold standard for laboratory inspection and diagnosis of malaria. Smear inspection is, however, time-consuming and dependent on trained microscopists with results varying in accuracy. We sought to develop an automated image analysis method to impro...
Autores principales: | Davidson, Mira S., Andradi-Brown, Clare, Yahiya, Sabrina, Chmielewski, Jill, O’Donnell, Aidan J., Gurung, Pratima, Jeninga, Myriam D., Prommana, Parichat, Andrew, Dean W., Petter, Michaela, Uthaipibull, Chairat, Boyle, Michelle J., Ashdown, George W., Dvorin, Jeffrey D., Reece, Sarah E., Wilson, Danny W., Cunningham, Kane A., Ando, D. Michael., Dimon, Michelle, Baum, Jake |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8724263/ https://www.ncbi.nlm.nih.gov/pubmed/35036920 http://dx.doi.org/10.1017/S2633903X21000015 |
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