Characterization of noise in long-term ECG monitoring with machine learning based on clinical criteria.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 61; no. 9; pp. 2227 - 2241 |
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| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Sep2023
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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=169849688&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 169849688 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Sep2023 vid: 61 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 169849688 162871854 10.1007/s11517-023-02802-5 169849688 ppf: 2227 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Characterization of noise in long-term ECG monitoring with machine learning based on clinical criteria. aug: au: Holgado-Cuadrado, Roberto Plaza-Seco, Carmen Lovisolo, Lisandro Blanco-Velasco, Manuel affil: Department for Signal Theory and Communications, Universidad de Alcalá, 28800, Alcalá de Henares, Madrid, Spain sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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