Smarter Alerts, Smaller Patients: AI‐Enhanced Implantable Loop Recorder Monitoring in Children.
This article evaluates Medtronic's AccuRhythm system, integrated with the LINQ II implantable loop recorder, for reducing atrial fibrillation and pause alerts in a pediatric cohort. In a study of 45 children, AccuRhythm decreased pause alerts by 75% and atrial fibrillation alerts by 11%, potentially...
| Publicado en: | Journal of Cardiovascular Electrophysiology Vol. 37; no. 8; pp. 1877 - 1879 |
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| Autor principal: | |
| Formato: | commentary editorial Journal Article |
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Wiley-Blackwell
Aug2026
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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=196220661&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 196220661 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10453873 GSB jtl: Journal of Cardiovascular Electrophysiology issn: 10453873 maglogo: Y pubinfo: dt: Aug2026 vid: 37 iid: 8 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 196220661 195143378 196220661 196220661 10.1111/jce.70425 196220661 ppf: 1877 ppct: 2 formats: tig: atl: Smarter Alerts, Smaller Patients: AI‐Enhanced Implantable Loop Recorder Monitoring in Children. aug: au: Asztalos, Ivor B. affil: Division of Pediatric Cardiology, Mayo Clinc, Rochester Minnesota, , USA sug: subj: Artificial Intelligence Defibrillators, Implantable Equipment and Supplies Atrial Fibrillation Diagnosis Electrocardiography, Ambulatory In Infancy and Childhood Equipment Alarm Systems Monitoring, Physiologic Serial Publications Machine Learning Algorithms Workflow Signal Processing, Computer Assisted Child Arrhythmia Child: 6-12 years ab: This article evaluates Medtronic's AccuRhythm system, integrated with the LINQ II implantable loop recorder, for reducing atrial fibrillation and pause alerts in a pediatric cohort. In a study of 45 children, AccuRhythm decreased pause alerts by 75% and atrial fibrillation alerts by 11%, potentially saving 58 clinic hours annually. The system combines an on-device rule-based algorithm (TruRhythm) with a cloud-based deep-learning model (AccuRhythm) to optimize alert accuracy and workflow efficiency. The article highlights the need for further validation of false positive and false negative rates, especially in pediatric populations where adult-developed algorithms may underperform. This research underscores the growing role of artificial intelligence in clinical electrophysiology to streamline monitoring without replacing core clinical judgment. pubtype: Academic Journal doctype: commentary editorial Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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