An interpretable machine learning model integrating mucosal and cellular immunity to predict SARS-CoV-2 reinfection: a multicenter cohort study.
Overview & Synopsis
Open access biomedical research article published in Emerg Microbes Infect.
Indexed from repository: PubMed Central
(
pmc.ncbi.nlm.nih.gov)
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Document Information
| Document Title | An interpretable machine learning model integrating mucosal and cellular immunity to predict SARS-CoV-2 reinfection: a multicenter cohort study. |
|---|---|
| Author / Organization | Ran J, Zhang W, Zhang W, Huang H, Gong L, Yin S, Chen Y, Wang A, Min H, Zhu L, Chu J, Qin Y, Huang R, Wu C, Chen Y |
| Subject & Discipline | Emerg Microbes Infect |
| Categories | Medicine & Health |
| Publication Year | 2026 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
PubMed Central
(pmc.ncbi.nlm.nih.gov)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-138931 |
| Original Source Link | Visit Source Page on pmc.ncbi.nlm.nih.gov » |