Accurate Classification of COVID-19 Based on Incomplete Heterogeneous Data using a KNN Variant Algorithm

Great efforts are now underway to control the coronavirus 2019 disease (COVID-19). Millions of people are medically examined, and their data keep piling up awaiting classification. The data are typically both incomplete and heterogeneous which hampers classical classification algorithms. Some resear...

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Detalles Bibliográficos
Autores principales: Hamed, Ahmed, Sobhy, Ahmed, Nassar, Hamed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Research Article-Computer Engineering and Computer Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7931985/
https://www.ncbi.nlm.nih.gov/pubmed/33688457
http://dx.doi.org/10.1007/s13369-020-05212-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7931985/
https://www.ncbi.nlm.nih.gov/pubmed/33688457
http://dx.doi.org/10.1007/s13369-020-05212-z

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