Der gesellschaftliche Mehrwert verknüpfter Daten: Algorithmen als Entscheidungs hilfen bei Antibiotikaverschreibungen
Year of publication: |
2021
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Authors: | Huang, Shan ; Ribers, Michael ; Ullrich, Hannes |
Published in: |
DIW Wochenbericht. - Berlin : Deutsches Institut für Wirtschaftsforschung (DIW), ISSN 1860-8787. - Vol. 88.2021, 13/14, p. 239-246
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Publisher: |
Berlin : Deutsches Institut für Wirtschaftsforschung (DIW) |
Subject: | antibiotic prescribing | prediction policy | administrative data | data combination |
Type of publication: | Article |
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Type of publication (narrower categories): | Article |
Language: | German |
Other identifiers: | 10.18723/diw_wb:2021-13-1 [DOI] 1755475446 [GVK] hdl:10419/233784 [Handle] |
Classification: | C10 - Econometric and Statistical Methods: General. General ; c55 ; I11 - Analysis of Health Care Markets ; I18 - Government Policy; Regulation; Public Health ; L38 - Public Policy ; O38 - Government Policy ; Q28 - Government Policy |
Source: |
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Huang, Shan, (2021)
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Battling antibiotic resistance: Can machine learning improve rescribing?
Ribers, Michael, (2019)
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Artificial intelligence and big data can help contain resistance to antibiotics
Ribers, Michael, (2019)
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The value of data for prediction policy problems: Evidence from antibiotic prescribing
Huang, Shan, (2021)
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The value of data for prediction policy problems : evidence from antibiotic prescribing
Huang, Shan, (2021)
-
Huang, Shan, (2021)
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