Using Artificial Intelligence in Infection Prevention
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Medicine
Link
http://link.springer.com/content/pdf/10.1007/s40506-020-00216-7.pdf
Reference31 articles.
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2. • Scott IA, Cook D, Coiera EW, Richards B. Machine learning in clinical practice: prospects and pitfalls. Med J Aust. 2019;211(5):203–5.e1. https://doi.org/10.5694/mja2.50294Short perspectives article with useful definitions and examples of machine learning applications and a discussion of their limitations in clinical practice.
3. •• Rajkomar A, Dean J, Kohane I. Machine learning in medicine. N Engl J Med. 2019;380(14):1347–58. https://doi.org/10.1056/NEJMra1814259Practical review article with supporting online video and audio interview. Definitions including how machine learning differs from traditional approaches, examples of how machine learning can augement patient care and summary of key concerns for clinicians.
4. Storr J, Twyman A, Zingg W, Damani N, Kilpatrick C, Reilly J, et al. Core components for effective infection prevention and control programmes: new WHO evidence-based recommendations. Antimicrob Resist Infect Control. 2017;6:6. https://doi.org/10.1186/s13756-016-0149-9.
5. Lopez-Garcia M, Kypraios T. A unified stochastic modelling framework for the spread of nosocomial infections. J R Soc Interface. 2018;15(143). https://doi.org/10.1098/rsif.2018.0060.
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