Prediction of symptomatic and asymptomatic bacteriuria in spinal cord injury patients using machine learning.
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| Title: | Prediction of symptomatic and asymptomatic bacteriuria in spinal cord injury patients using machine learning. |
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| Authors: | Hoque MM; Australian Institute for Microbiology & Infection, University of Technology Sydney, Sydney, NSW, Australia., Noorian P; Australian Institute for Microbiology & Infection, University of Technology Sydney, Sydney, NSW, Australia., Espinoza-Vergara G; Australian Institute for Microbiology & Infection, University of Technology Sydney, Sydney, NSW, Australia., To J; Australian Institute for Microbiology & Infection, University of Technology Sydney, Sydney, NSW, Australia., Leo D; Australian Institute for Microbiology & Infection, University of Technology Sydney, Sydney, NSW, Australia., Chari P; Spinal Cord Injury Unit, Royal North Shore Hospital, Sydney, NSW, Australia., Weber G; Royal Rehab Group, Sydney, NSW, Australia., Pryor J; Royal Rehab Group, Sydney, NSW, Australia.; Susan Wakil School of Nursing and Midwifery, University of Sydney, Sydney, Australia., Duggin IG; Australian Institute for Microbiology & Infection, University of Technology Sydney, Sydney, NSW, Australia., Lee BB; Department of Spinal and Rehabilitation Medicine, Prince of Wales Hospital, Sydney, NSW, Australia.; Neuroscience Research Australia (NEURA), Sydney, NSW, Australia., Rice SA; Australian Institute for Microbiology & Infection, University of Technology Sydney, Sydney, NSW, Australia. Scott.Rice@csiro.au.; CSIRO, Microbiomes for One Systems Health, Agriculture & Food, Westmead, NSW, Australia. Scott.Rice@csiro.au., McDougald D; Australian Institute for Microbiology & Infection, University of Technology Sydney, Sydney, NSW, Australia. diane.mcdougald@uts.edu.au. |
| Source: | Microbiome [Microbiome] 2025 Nov 27; Vol. 13 (1), pp. 246. Date of Electronic Publication: 2025 Nov 27. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: BioMed Central Country of Publication: England NLM ID: 101615147 Publication Model: Electronic Cited Medium: Internet ISSN: 2049-2618 (Electronic) Linking ISSN: 20492618 NLM ISO Abbreviation: Microbiome Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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