Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?
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- Michael Allan Ribers & Hannes Ullrich, 2019. "Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?," Papers 1906.03044, arXiv.org.
- Michael Allan Ribers & Hannes Ullrich, 2019. "Battling antibiotic resistance: can machine learning improve prescribing?," CESifo Working Paper Series 7654, CESifo Group Munich.
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More about this item
KeywordsAntibiotic prescribing; prediction policy; machine learning; expert decision-making;
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
- I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
- I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
- L38 - Industrial Organization - - Nonprofit Organizations and Public Enterprise - - - Public Policy
- O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy
- Q28 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Government Policy
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-BIG-2019-05-13 (Big Data)
- NEP-CMP-2019-05-13 (Computational Economics)
- NEP-EUR-2019-05-13 (Microeconomic European Issues)
- NEP-HEA-2019-05-13 (Health Economics)
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