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...

Deskribapen osoa

Gorde:
Xehetasun bibliografikoak
Argitaratua izan da:Malar J
Egile Nagusiak: 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
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: BioMed Central 2021
Gaiak:
Research
Sarrera elektronikoa: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
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