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Machine learning prediction of sepsis in paralytic ileus using interpretable clinical models.

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Title: Machine learning prediction of sepsis in paralytic ileus using interpretable clinical models.
Authors: Song Q; Division of Colorectal & Anal Surgery, Department of Gastrointestinal Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, China., Wu X; Department of Breast Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, China., Taheri FA; Division of Colorectal & Anal Surgery, Department of Gastrointestinal Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, China., Meng L; Division of Colorectal & Anal Surgery, Department of Gastrointestinal Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, China., Wang W; Division of Colorectal & Anal Surgery, Department of Gastrointestinal Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, China., Mo X; Division of Colorectal & Anal Surgery, Department of Gastrointestinal Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, China.
Source: Frontiers in cellular and infection microbiology [Front Cell Infect Microbiol] 2026 Jun 02; Vol. 16, pp. 1705126. Date of Electronic Publication: 2026 Jun 02 (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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  Data: Machine learning prediction of sepsis in paralytic ileus using interpretable clinical models.
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  Data: <searchLink fieldCode="AU" term="%22Song+Q%22">Song Q</searchLink>; Division of Colorectal & Anal Surgery, Department of Gastrointestinal Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, China.<br /><searchLink fieldCode="AU" term="%22Wu+X%22">Wu X</searchLink>; Department of Breast Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, China.<br /><searchLink fieldCode="AU" term="%22Taheri+FA%22">Taheri FA</searchLink>; Division of Colorectal & Anal Surgery, Department of Gastrointestinal Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, China.<br /><searchLink fieldCode="AU" term="%22Meng+L%22">Meng L</searchLink>; Division of Colorectal & Anal Surgery, Department of Gastrointestinal Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, China.<br /><searchLink fieldCode="AU" term="%22Wang+W%22">Wang W</searchLink>; Division of Colorectal & Anal Surgery, Department of Gastrointestinal Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, China.<br /><searchLink fieldCode="AU" term="%22Mo+X%22">Mo X</searchLink>; Division of Colorectal & Anal Surgery, Department of Gastrointestinal Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, China.
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  Data: <searchLink fieldCode="JN" term="%22101585359%22">Frontiers in cellular and infection microbiology</searchLink> [Front Cell Infect Microbiol] 2026 Jun 02; Vol. 16, pp. 1705126. <i>Date of Electronic Publication: </i>2026 Jun 02 (<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.2026.1705126
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      – Code: eng
        Text: English
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      – TitleFull: Machine learning prediction of sepsis in paralytic ileus using interpretable clinical models.
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            NameFull: Song Q
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            NameFull: Wu X
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              Text: 2026 Jun 02
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