Modeling global and local label correlation with graph convolutional networks for multi-label chest X-ray image classification.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 60; no. 9; pp. 2567 - 2589 |
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| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Sep2022
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| 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=158447320&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 158447320 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Sep2022 vid: 60 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 158447320 157792026 10.1007/s11517-022-02604-1 158447320 ppf: 2567 ppct: 22 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Modeling global and local label correlation with graph convolutional networks for multi-label chest X-ray image classification. aug: au: Li, Lanting Cao, Peng Yang, Jinzhu Zaiane, Osmar R. affil: Computer Science and Engineering, Northeastern University, Shenyang, China sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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