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- Q102373653 description "2020 ވަނަ އަހަރުގެ ނޮވެމްބަރުމަހުގެ 24ވަނަ ދުވަހު ޝާއިރުކުރެވުނު ސައިންޓިފިކް ލިޔުމެއް" @default.
- Q102373653 description "artículu científicu espublizáu en payares de 2020" @default.
- Q102373653 description "bài báo khoa học" @default.
- Q102373653 description "scientific article published on 24 November 2020" @default.
- Q102373653 description "wetenschappelijk artikel" @default.
- Q102373653 description "наукова стаття, опублікована 24 листопада 2020" @default.
- Q102373653 description "գիտական հոդված հրատարակված 2020 թվականի նոյեմբերի 24-ին" @default.
- Q102373653 name "How to produce sound predictions of incidence at a district level using either health care or mortality data in the absence of a national registry: the example of cancer in France" @default.
- Q102373653 name "How to produce sound predictions of incidence at a district level using either health care or mortality data in the absence of a national registry: the example of cancer in France" @default.
- Q102373653 name "How to produce sound predictions of incidence at a district level using either health care or mortality data in the absence of a national registry: the example of cancer in France" @default.
- Q102373653 type Item @default.
- Q102373653 label "How to produce sound predictions of incidence at a district level using either health care or mortality data in the absence of a national registry: the example of cancer in France" @default.
- Q102373653 label "How to produce sound predictions of incidence at a district level using either health care or mortality data in the absence of a national registry: the example of cancer in France" @default.
- Q102373653 label "How to produce sound predictions of incidence at a district level using either health care or mortality data in the absence of a national registry: the example of cancer in France" @default.
- Q102373653 prefLabel "How to produce sound predictions of incidence at a district level using either health care or mortality data in the absence of a national registry: the example of cancer in France" @default.
- Q102373653 prefLabel "How to produce sound predictions of incidence at a district level using either health care or mortality data in the absence of a national registry: the example of cancer in France" @default.
- Q102373653 prefLabel "How to produce sound predictions of incidence at a district level using either health care or mortality data in the absence of a national registry: the example of cancer in France" @default.
- Q102373653 P1433 Q102373653-83BA8EA1-955E-4D7F-8C11-13B17328CAD4 @default.
- Q102373653 P1476 Q102373653-7AA00D48-FD72-43C2-B06F-9F8BD8541D85 @default.
- Q102373653 P2093 Q102373653-7E88F1FD-1314-44E5-8011-3FCA28E62200 @default.
- Q102373653 P2093 Q102373653-824D7148-BC6D-4BBE-B08A-696B32E63C3F @default.
- Q102373653 P2093 Q102373653-D651DC7C-8B47-4773-8FA4-3884E751FF2B @default.
- Q102373653 P2093 Q102373653-D6D4966F-8723-4E7E-9515-99F83FAA7DE2 @default.
- Q102373653 P2093 Q102373653-F50B4BCC-06C8-4663-AE60-2B19C7F1C932 @default.
- Q102373653 P31 Q102373653-D69D6702-BB63-4C1D-8D54-F576324ED680 @default.
- Q102373653 P356 Q102373653-915FF690-9EB1-4337-A913-14C9A0DD5854 @default.
- Q102373653 P577 Q102373653-A9C6D7D9-EE21-41A4-B727-3FBBABA57A6F @default.
- Q102373653 P698 Q102373653-6EC2D5FC-5DA5-4261-A884-ABB6BE4A214F @default.
- Q102373653 P356 DYAA217 @default.
- Q102373653 P698 33232469 @default.
- Q102373653 P1433 Q6051393 @default.
- Q102373653 P1476 "How to produce sound predictions of incidence at a district level using either health care or mortality data in the absence of a national registry: the example of cancer in France" @default.
- Q102373653 P2093 "Edouard Chatignoux" @default.
- Q102373653 P2093 "Laurent Remontet" @default.
- Q102373653 P2093 "Marc Colonna" @default.
- Q102373653 P2093 "Pascale Grosclaude" @default.
- Q102373653 P2093 "Zoé Uhry" @default.
- Q102373653 P31 Q13442814 @default.
- Q102373653 P356 "10.1093/IJE/DYAA217" @default.
- Q102373653 P577 "2020-11-24T00:00:00Z" @default.
- Q102373653 P698 "33232469" @default.