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For: Li BY, Oh J, Young VB, Rao K, Wiens J. Using Machine Learning and the Electronic Health Record to Predict Complicated Clostridium difficile Infection. Open Forum Infect Dis 2019;6:ofz186. [PMID: 31139672 DOI: 10.1093/ofid/ofz186] [Cited by in Crossref: 18] [Cited by in F6Publishing: 16] [Article Influence: 6.0] [Reference Citation Analysis]
Number Citing Articles
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2 Park J, Bonde PN. Machine Learning in Cardiac Surgery: Predicting Mortality and Readmission. ASAIO J 2022. [PMID: 35544455 DOI: 10.1097/MAT.0000000000001696] [Reference Citation Analysis]
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4 Vandenberg O, Durand G, Hallin M, Diefenbach A, Gant V, Murray P, Kozlakidis Z, van Belkum A. Consolidation of Clinical Microbiology Laboratories and Introduction of Transformative Technologies. Clin Microbiol Rev 2020;33:e00057-19. [PMID: 32102900 DOI: 10.1128/CMR.00057-19] [Cited by in Crossref: 14] [Cited by in F6Publishing: 7] [Article Influence: 7.0] [Reference Citation Analysis]
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6 Peiffer-Smadja N, Rawson TM, Ahmad R, Buchard A, Georgiou P, Lescure FX, Birgand G, Holmes AH. Machine learning for clinical decision support in infectious diseases: a narrative review of current applications. Clin Microbiol Infect 2020;26:584-95. [PMID: 31539636 DOI: 10.1016/j.cmi.2019.09.009] [Cited by in Crossref: 37] [Cited by in F6Publishing: 26] [Article Influence: 12.3] [Reference Citation Analysis]
7 Huang F, Brouqui P, Boudjema S. How does innovative technology impact nursing in infectious diseases and infection control? A scoping review. Nurs Open 2021;8:2369-84. [PMID: 33765353 DOI: 10.1002/nop2.863] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
8 Wang P, Cheng S, Li Y, Liu L, Liu J, Zhao Q, Luo S. Prediction of Lumbar Drainage-Related Meningitis Based on Supervised Machine Learning Algorithms. Front Public Health 2022;10:910479. [DOI: 10.3389/fpubh.2022.910479] [Reference Citation Analysis]
9 Egli A, Schrenzel J, Greub G. Digital microbiology. Clin Microbiol Infect 2020;26:1324-31. [PMID: 32603804 DOI: 10.1016/j.cmi.2020.06.023] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
10 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]
11 Wu Q, Savidge TC. Systems approaches for the clinical diagnosis of Clostridioides difficile infection. Transl Res 2020;220:57-67. [PMID: 32272094 DOI: 10.1016/j.trsl.2020.03.006] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
12 Stevens VW, Shoemaker HE, Jones MM, Jones BE, Nelson RE, Khader K, Samore MH, Rubin MA. Validation of the SHEA/IDSA severity criteria to predict poor outcomes among inpatients and outpatients with Clostridioides difficile infection. Infect Control Hosp Epidemiol 2020;41:510-6. [PMID: 31996280 DOI: 10.1017/ice.2020.8] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
13 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]
14 Tyler J, Choi SW, Tewari M. Real-time, personalized medicine through wearable sensors and dynamic predictive modeling: a new paradigm for clinical medicine. Curr Opin Syst Biol 2020;20:17-25. [PMID: 32984661 DOI: 10.1016/j.coisb.2020.07.001] [Cited by in Crossref: 10] [Cited by in F6Publishing: 7] [Article Influence: 5.0] [Reference Citation Analysis]
15 Juneja D, Gupta A, Singh O. Artificial intelligence in critically ill diabetic patients: current status and future prospects. Artif Intell Gastroenterol 2022; 3(2): 66-79 [DOI: 10.35712/aig.v3.i2.66] [Reference Citation Analysis]
16 Kuula LSM, Backman JT, Blom ML. Healthcare costs and mortality associated with serious fluoroquinolone-related adverse reactions. Pharmacol Res Perspect 2022;10:e00931. [PMID: 35170862 DOI: 10.1002/prp2.931] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
17 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. Am J Infect Control 2022;50:250-7. [PMID: 35067382 DOI: 10.1016/j.ajic.2021.11.012] [Reference Citation Analysis]
18 Tang S, Davarmanesh P, Song Y, Koutra D, Sjoding MW, Wiens J. Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data. J Am Med Inform Assoc 2020;27:1921-34. [PMID: 33040151 DOI: 10.1093/jamia/ocaa139] [Cited by in Crossref: 7] [Cited by in F6Publishing: 4] [Article Influence: 7.0] [Reference Citation Analysis]
19 Beauregard-Paultre C, Abou Chakra CN, McGeer A, Labbé AC, Simor AE, Gold W, Muller MP, Powis J, Katz K, Cadarette SM, Pépin J, Valiquette L. External validation of clinical prediction rules for complications and mortality following Clostridioides difficile infection. PLoS One 2019;14:e0226672. [PMID: 31846487 DOI: 10.1371/journal.pone.0226672] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 1.7] [Reference Citation Analysis]
20 Alqaissi EY, Alotaibi FS, Ramzan MS. Modern Machine-Learning Predictive Models for Diagnosing Infectious Diseases. Comput Math Methods Med 2022;2022:6902321. [PMID: 35693267 DOI: 10.1155/2022/6902321] [Reference Citation Analysis]
21 Barchitta M, Maugeri A, Favara G, Riela PM, Gallo G, Mura I, Agodi A; SPIN-UTI Network. A machine learning approach to predict healthcare-associated infections at intensive care unit admission: findings from the SPIN-UTI project. J Hosp Infect 2021;112:77-86. [PMID: 33676936 DOI: 10.1016/j.jhin.2021.02.025] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
22 Luz CF, Vollmer M, Decruyenaere J, Nijsten MW, Glasner C, Sinha B. Machine learning in infection management using routine electronic health records: tools, techniques, and reporting of future technologies. Clin Microbiol Infect 2020;26:1291-9. [PMID: 32061798 DOI: 10.1016/j.cmi.2020.02.003] [Cited by in Crossref: 23] [Cited by in F6Publishing: 11] [Article Influence: 11.5] [Reference Citation Analysis]
23 Perry DA, Shirley D, Micic D, Patel CP, Putler R, Menon A, Young VB, Rao K. External Validation and Comparison of Clostridioides difficile Severity Scoring Systems. Clin Infect Dis 2021:ciab737. [PMID: 34459885 DOI: 10.1093/cid/ciab737] [Reference Citation Analysis]