Accurate Classification of COVID-19 Based on Incomplete Heterogeneous Data using a
COVID-19 diagnosis
Euclidean
Heterogeneous data
Incomplete data
KNN
Mahalanobis
Rough set theory
Journal
Arabian journal for science and engineering
ISSN: 2193-567X
Titre abrégé: Arab J Sci Eng
Pays: Germany
ID NLM: 101698714
Informations de publication
Date de publication:
2021
2021
Historique:
received:
08
06
2020
accepted:
07
12
2020
pubmed:
11
3
2021
medline:
11
3
2021
entrez:
10
3
2021
Statut:
ppublish
Résumé
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 researchers have recently modified the popular
Identifiants
pubmed: 33688457
doi: 10.1007/s13369-020-05212-z
pii: 5212
pmc: PMC7931985
doi:
Types de publication
Journal Article
Langues
eng
Pagination
8261-8272Informations de copyright
© King Fahd University of Petroleum & Minerals 2020.
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