Machine learning models integrating dietary data predict all-cause mortality in U.S. NAFLD patients: an NHANES-based study.
| Publicado en: | Nutrition Journal Vol. 24; no. 1; pp. 1 - 13 |
|---|---|
| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
BioMed Central
7/1/2025
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=186308374&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 186308374 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14752891 1CYY jtl: Nutrition Journal issn: 14752891 maglogo: N pubinfo: dt: 7/1/2025 vid: 24 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 186308374 10.1186/s12937-025-01170-0 186308374 ppf: 1 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Machine learning models integrating dietary data predict all-cause mortality in U.S. NAFLD patients: an NHANES-based study. aug: au: Chen, Pinchu Li, Yao Yang, Chenfenglin Zhang, Qifan affil: https://ror.org/01eq10738 Division of Hepatobiliopancreatic Surgery, Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
|---|