An efficient network with state space model under evidential training for fetal echocardiography standard view recognition.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 63; no. 9; pp. 2693 - 2707 |
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| Autores principales: | , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Sep2025
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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=187673844&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 187673844 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Sep2025 vid: 63 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 187673844 184189233 10.1007/s11517-025-03347-5 187673844 ppf: 2693 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: An efficient network with state space model under evidential training for fetal echocardiography standard view recognition. aug: au: Chen, Changzhao Liu, Yiman Liang, Tongtong Lin, Shibin Han, Xiaoxiang Liu, Xiaohong Yang, Jing Zhang, Yuqi Yan, Xueping affil: https://ror.org/01x48j266 Department of Ultrasound Medicine, Hainan Women and Children'S Medical Center, Haikou, China sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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