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Urine volatile organic compounds profiling via GC-IMS combined with machine learning: a powerful diagnostic and pathogen differentiation tool for urinary tract infections.

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Title: Urine volatile organic compounds profiling via GC-IMS combined with machine learning: a powerful diagnostic and pathogen differentiation tool for urinary tract infections.
Authors: Zheng X; Department of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, Shandong, China., Sun X; Department of Clinical Laboratory, Jiyang People's Hospital of Jinan, Jinan, Shandong, China., Du W; Department of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, Shandong, China., Sun S; Department of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, Shandong, China., Chen D; Department of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, Shandong, China., Cheng W; Department of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, Shandong, China., Zhuang X; Department of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, Shandong, China., Zhang Y; Department of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, Shandong, China.
Source: Frontiers in cellular and infection microbiology [Front Cell Infect Microbiol] 2026 Feb 11; Vol. 16, pp. 1745468. Date of Electronic Publication: 2026 Feb 11 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Media SA Country of Publication: Switzerland NLM ID: 101585359 Publication Model: eCollection Cited Medium: Internet ISSN: 2235-2988 (Electronic) Linking ISSN: 22352988 NLM ISO Abbreviation: Front Cell Infect Microbiol Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:2235-2988
DOI:10.3389/fcimb.2026.1745468