ARIMA model for predicting chronic kidney disease and estimating its economic burden in China
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1471-2458
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
ARIMA model for predicting chronic kidney disease and estimating its economic burden in China ; volume:22 ; number:1 ; day:30 ; month:12 ; year:2022 ; pages:1-9 ; date:12.2022
BMC public health ; 22, Heft 1 (30.12.2022), 1-9, 12.2022
- Klassifikation
-
Wirtschaft
- Urheber
-
Jian, Yining
Zhu, Di
Zhou, Dongnan
Li, Nana
Du, Han
Dong, Xue
Fu, Xuemeng
Tao, Dong
Han, Bing
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1186/s12889-022-14959-z
- URN
-
urn:nbn:de:101:1-2023031109131972450062
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:48 MESZ
Datenpartner
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Beteiligte
- Jian, Yining
- Zhu, Di
- Zhou, Dongnan
- Li, Nana
- Du, Han
- Dong, Xue
- Fu, Xuemeng
- Tao, Dong
- Han, Bing
- SpringerLink (Online service)
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