Machine learning approaches classify clinical malaria outcomes based on haematological parameters

BACKGROUND: Malaria is still a major global health burden, with more than 3.2 billion people in 91 countries remaining at risk of the disease. Accurately distinguishing malaria from other diseases, especially uncomplicated malaria (UM) from non-malarial infections (nMI), remains a challenge. Further...

詳細記述

保存先:
書誌詳細
出版年:BMC Med
主要な著者: Morang’a, Collins M., Amenga–Etego, Lucas, Bah, Saikou Y., Appiah, Vincent, Amuzu, Dominic S. Y., Amoako, Nicholas, Abugri, James, Oduro, Abraham R., Cunnington, Aubrey J., Awandare, Gordon A., Otto, Thomas D.
フォーマット: Artigo
言語:Inglês
出版事項: BioMed Central 2020
主題:
Research Article
オンライン･アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC7702702/
https://ncbi.nlm.nih.gov/pubmed/33250058
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12916-020-01823-3
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