Self-knowledge distillation for prediction of breast cancer molecular subtypes based on digital breast tomosynthesis.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 63; no. 11; pp. 3169 - 3184 |
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| Autores principales: | , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Nov2025
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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=189590704&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 189590704 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Nov2025 vid: 63 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 189590704 185618183 10.1007/s11517-025-03383-1 189590704 ppf: 3169 ppct: 15 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Self-knowledge distillation for prediction of breast cancer molecular subtypes based on digital breast tomosynthesis. aug: au: Guo, Wei Bo, Jiayi Chen, Shilin Gong, Zhaoxuan Zhang, Guodong Zhou, Hanxun Wang, Zekun Zhao, Peng Jiang, Wenyan affil: https://ror.org/02423gm04 School of Computer, Shenyang Aerospace University, 110122, Shenyang, Liaoning, China sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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