Prediction of risk of acquiring urinary tract infection during hospital stay based on machine-learning: A retrospective cohort study
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DOI: 10.1371/journal.pone.0248636
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References listed on IDEAS
- Li Luo & Jialing Li & Chuang Liu & Wenwu Shen, 2019. "Using machine‐learning methods to support health‐care professionals in making admission decisions," International Journal of Health Planning and Management, Wiley Blackwell, vol. 34(2), pages 1236-1246, April.
- R Andrew Taylor & Christopher L Moore & Kei-Hoi Cheung & Cynthia Brandt, 2018. "Predicting urinary tract infections in the emergency department with machine learning," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-15, March.
- Kristin M Corey & Sehj Kashyap & Elizabeth Lorenzi & Sandhya A Lagoo-Deenadayalan & Katherine Heller & Krista Whalen & Suresh Balu & Mitchell T Heflin & Shelley R McDonald & Madhav Swaminathan & Mark , 2018. "Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): A retrospective, single-site study," PLOS Medicine, Public Library of Science, vol. 15(11), pages 1-19, November.
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