Deep learning-based malaria parasite detection: convolutional neural networks model for accurate spe...
Deep learning-based malaria parasite detection: convolutional neural networks model for accurate species identification of Plasmodium falciparum and Plasmodium vivax
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London: Nature Publishing Group UK
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Language
English
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London: Nature Publishing Group UK
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Accurate malaria diagnosis with precise identification of
Plasmodium
species is crucial for an effective treatment. While microscopy is still the gold standard in malaria diagnosis, it relies heavily on trained personnel. Artificial intelligence (AI) advances, particularly convolutional neural networks (CNNs), have significantly improved diag...
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Deep learning-based malaria parasite detection: convolutional neural networks model for accurate species identification of Plasmodium falciparum and Plasmodium vivax
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TN_cdi_doaj_primary_oai_doaj_org_article_a0ffbcaa59ab46e9801d435f8ad5d634
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_a0ffbcaa59ab46e9801d435f8ad5d634
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ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-025-87979-5
