Artificial intelligence‐augmented ECG assessment: The promise and the challenge.
| Publicado en: | Journal of Cardiovascular Electrophysiology Vol. 30; no. 5; pp. 675 - 679 |
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| Autor principal: | |
| Formato: | commentary editorial Journal Article |
| Publicado: |
Wiley-Blackwell
May2019
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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=136838479&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 136838479 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10453873 GSB jtl: Journal of Cardiovascular Electrophysiology issn: 10453873 maglogo: Y pubinfo: dt: May2019 vid: 30 iid: 5 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 136838479 136838479 136838479 10.1111/jce.13891 136838479 ppf: 675 ppct: 4 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Artificial intelligence‐augmented ECG assessment: The promise and the challenge. aug: au: Anderson, Kelley P. affil: Department of Cardiology, Marshfield Clinic, Marshfield Wisconsin sug: subj: Ventricular Dysfunction, Left Diagnosis Deep Learning Methods Electrocardiography Methods Algorithms Evaluation Natriuretic Peptide, Brain Blood Heart Failure Sensitivity and Specificity False Positive Results Serial Publications Ventricular Ejection Fraction Hypertrophy, Left Ventricular Diagnosis pubtype: Academic Journal doctype: commentary editorial Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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