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Jurnal

Cardiovascular Digital Health Journal

Scopus

ISSN 2666-6936 · Elsevier · 179 artikel di indeks

  1. Artikel Jurnal

    Thank You to Reviewers

    Cardiovascular Digital Health Journal, Vol. 4 No. 1 · 2023 · Inggris · DOAJ Scopus

  2. Artikel Jurnal

    Validating cuffless continuous blood pressure monitoring devices

    Jiun-Ruey Hu, MD, MPH; Gabrielle Martin, BS; Sanjna Iyengar, BS dkk.

    Cardiovascular Digital Health Journal, Vol. 4 No. 1 · 2023 · Inggris · DOAJ Scopus

    Cuff-based home blood pressure (BP) devices, which have been the standard for BP monitoring for decades, are limited by physical discomfort, convenience, and their ability to capture BP variability and patterns between intermittent readings. In recent years, cuffless BP devices, which do not…

  3. Artikel Jurnal

    Journal Editorial Board

    Cardiovascular Digital Health Journal, Vol. 4 No. 1 · 2023 · Inggris · DOAJ Scopus

  4. Artikel Jurnal

    Clinician use of data elements from cardiovascular implantable electronic devices in clinical practice

    Carly Daley, PhD; Amanda Coupe, BA; Tina Allmandinger, RN, BSN dkk.

    Cardiovascular Digital Health Journal, Vol. 4 No. 1 · 2023 · Inggris · DOAJ Scopus

    Background: Cardiovascular implantable electronic devices (CIEDs) capture an abundance of data for clinicians to review and integrate into the clinical decision-making process. The multitude of data from different device types and vendors presents challenges for viewing and using the data in…

  5. Artikel Jurnal

    Accurate QT correction method from transfer entropy

    Esa Räsänen, PhD; Teemu Pukkila; Matias Kanniainen dkk.

    Cardiovascular Digital Health Journal, Vol. 4 No. 1 · 2023 · Inggris · DOAJ Scopus

    Background: The QT interval in the electrocardiogram (ECG) is a fundamental risk measure for arrhythmic adverse cardiac events. However, the QT interval depends on the heart rate and must be corrected accordingly. The present QT correction (QTc) methods are either simple models leading to under- or…

  6. Artikel Jurnal

    Artificial intelligence–enabled mobile electrocardiograms for event prediction in paroxysmal atrial fibrillation

    Ananditha Raghunath, MS; Dan D. Nguyen, MD; Matthew Schram, PhD dkk.

    Cardiovascular Digital Health Journal, Vol. 4 No. 1 · 2023 · Inggris · DOAJ Scopus

    Background: Paroxysmal atrial fibrillation (AF) often eludes early diagnosis, resulting in significant morbidity and mortality. Artificial intelligence (AI) has been used to predict AF from sinus rhythm electrocardiograms (ECGs), but AF prediction using sinus rhythm mobile electrocardiograms (mECG)…