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For: Marra AR, Alzunitan M, Abosi O, Edmond MB, Street WN, Cromwell JW, Salinas JL. Modest Clostridiodes difficile infection prediction using machine learning models in a tertiary care hospital. Diagn Microbiol Infect Dis 2020;98:115104. [PMID: 32650284 DOI: 10.1016/j.diagmicrobio.2020.115104] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
Number Citing Articles
1 Brodzicki A, Jaworek-Korjakowska J, Kleczek P, Garland M, Bogyo M. Pre-Trained Deep Convolutional Neural Network for Clostridioides Difficile Bacteria Cytotoxicity Classification Based on Fluorescence Images. Sensors (Basel) 2020;20:E6713. [PMID: 33255305 DOI: 10.3390/s20236713] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
2 Chen Y, Xi M, Johnson A, Tomlinson G, Campigotto A, Chen L, Sung L. Machine Learning Approaches to Investigate Clostridioides difficile Infection and Outcomes: A Systematic Review. International Journal of Medical Informatics 2022. [DOI: 10.1016/j.ijmedinf.2022.104706] [Reference Citation Analysis]
3 Panchavati S, Zelin NS, Garikipati A, Pellegrini E, Iqbal Z, Barnes G, Hoffman J, Calvert J, Mao Q, Das R. A comparative analysis of machine learning approaches to predict C. difficile infection in hospitalized patients. American Journal of Infection Control 2022. [DOI: 10.1016/j.ajic.2021.11.012] [Reference Citation Analysis]