Künstliche Intelligenz und Daten können bei der Eindämmung von Antibiotikaresistenzen helfen
Year of publication: |
2019
|
---|---|
Authors: | Ribers, Michael ; Ullrich, Hannes |
Published in: |
DIW-Wochenbericht : Wirtschaft, Politik, Wissenschaft. - Berlin : DIW, ISSN 1860-8787, ZDB-ID 2029233-8. - Vol. 86.2019, 19, p. 335-341
|
Subject: | antibiotic prescribing | prediction policy | machine learning | expert decision-making |
Type of publication: | Article |
---|---|
Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
Language: | German |
Other identifiers: | 10.18723/diw_wb:2019-19-1 [DOI] hdl:10419/198021 [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 ; Q28 - Government Policy |
Source: | ECONIS - Online Catalogue of the ZBW |
-
Battling antibiotic resistance : can machine learning improve prescribing?
Ribers, Michael Allan, (2019)
-
Battling antibiotic resistance : can machine learning improve rescribing?
Ribers, Michael, (2019)
-
Artificial intelligence and big data can help contain resistance to antibiotics
Ribers, Michael, (2019)
- More ...
-
Battling antibiotic resistance: Can machine learning improve rescribing?
Ribers, Michael, (2019)
-
Artificial intelligence and big data can help contain resistance to antibiotics
Ribers, Michael, (2019)
-
Künstliche Intelligenz und Daten können bei der Eindämmung von Antibiotikaresistenzen helfen
Ribers, Michael, (2019)
- More ...