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
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  Data: 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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  Data: <searchLink fieldCode="AU" term="%22Zheng+X%22">Zheng X</searchLink>; Department of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, Shandong, China.<br /><searchLink fieldCode="AU" term="%22Sun+X%22">Sun X</searchLink>; Department of Clinical Laboratory, Jiyang People's Hospital of Jinan, Jinan, Shandong, China.<br /><searchLink fieldCode="AU" term="%22Du+W%22">Du W</searchLink>; Department of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, Shandong, China.<br /><searchLink fieldCode="AU" term="%22Sun+S%22">Sun S</searchLink>; Department of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, Shandong, China.<br /><searchLink fieldCode="AU" term="%22Chen+D%22">Chen D</searchLink>; Department of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, Shandong, China.<br /><searchLink fieldCode="AU" term="%22Cheng+W%22">Cheng W</searchLink>; Department of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, Shandong, China.<br /><searchLink fieldCode="AU" term="%22Zhuang+X%22">Zhuang X</searchLink>; Department of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, Shandong, China.<br /><searchLink fieldCode="AU" term="%22Zhang+Y%22">Zhang Y</searchLink>; Department of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, Shandong, China.
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  Data: <searchLink fieldCode="JN" term="%22101585359%22">Frontiers in cellular and infection microbiology</searchLink> [Front Cell Infect Microbiol] 2026 Feb 11; Vol. 16, pp. 1745468. <i>Date of Electronic Publication: </i>2026 Feb 11 (<i>Print Publication: </i>2026).
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Frontiers+Media+SA%22">Frontiers Media SA </searchLink><i>Country of Publication: </i>Switzerland <i>NLM ID: </i>101585359 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Internet <i>ISSN: </i>2235-2988 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2222352988%22">22352988 </searchLink><i>NLM ISO Abbreviation: </i>Front Cell Infect Microbiol <i>Subsets: </i>MEDLINE
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        Value: 10.3389/fcimb.2026.1745468
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      – TitleFull: 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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              Text: 2026 Feb 11
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