Innovative use of data sources: a cross-sectional study of data linkage and artificial intelligence practices across European countries

Innovative use of data sources: a cross-sectional study of data linkage and artificial intelligence practices across European countries

Abstract Background The availability of data generated from different sources is increasing with the possibility to link these data sources with each other. However, linked administrative data can be complex to use and may require advanced expertise and skills in statistical analysis. The main objec...

詳細記述

書誌詳細
主要な著者: Romana Haneef, Marie Delnord, Michel Vernay, Emmanuelle Bauchet, Rita Gaidelyte, Herman Van Oyen, Zeynep Or, Beatriz Pérez-Gómez, Luigi Palmieri, Peter Achterberg, Mariken Tijhuis, Metka Zaletel, Stefan Mathis-Edenhofer, Ondřej Májek, Håkon Haaheim, Hanna Tolonen, Anne Gallay
フォーマット: 論文
言語:English
出版事項: BMC 2020-06-01
シリーズ:Archives of Public Health
主題:
Innovation
Linked data
Artificial intelligence
Machine learning technique
Health status monitoring
Public health surveillance
オンライン･アクセス:http://link.springer.com/article/10.1186/s13690-020-00436-9

インターネット

http://link.springer.com/article/10.1186/s13690-020-00436-9

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