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. |
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| 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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| ISSN: | 2235-2988 |
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| DOI: | 10.3389/fcimb.2026.1705126 |
