Single-cell Sequence Analysis Combined with Multiple Machine Learning to Identify Markers in Sepsis Patients: LILRA5.
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| Title: | Single-cell Sequence Analysis Combined with Multiple Machine Learning to Identify Markers in Sepsis Patients: LILRA5. |
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| Authors: | Ning J; Department of Immunology, Immunology Department of Hebei Medical University, Shijiazhuang, People's Republic of China., Fan X; Department of Immunology, Immunology Department of Hebei Medical University, Shijiazhuang, People's Republic of China., Sun K; Department of Immunology, Immunology Department of Hebei Medical University, Shijiazhuang, People's Republic of China., Wang X; Department of Immunology, Immunology Department of Hebei Medical University, Shijiazhuang, People's Republic of China.; Department of Laboratory, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China., Li H; Department of Immunology, Immunology Department of Hebei Medical University, Shijiazhuang, People's Republic of China., Jia K; Department of Pathology, Pathology Department of Shijiazhuang People's Hospital, Shijiazhuang, People's Republic of China., Ma C; Department of Immunology, Immunology Department of Hebei Medical University, Shijiazhuang, People's Republic of China. macuiqing@hebmu.edu.cn. |
| Source: | Inflammation [Inflammation] 2023 Aug; Vol. 46 (4), pp. 1236-1254. Date of Electronic Publication: 2023 Mar 15. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Kluwer Academic/Plenum Publishers Country of Publication: United States NLM ID: 7600105 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-2576 (Electronic) Linking ISSN: 03603997 NLM ISO Abbreviation: Inflammation Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1573-2576 |
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| DOI: | 10.1007/s10753-023-01803-8 |
