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European Heart Journal - Digital Health is a peer-reviewed journal published by Oxford University Press, covering ECG Monitoring and Analysis, Atrial Fibrillation Management and Outcomes, Cardiovascular Function and Risk Factors.
| Publisher | Oxford University Press |
|---|---|
| Reference style | Author–year (OUP) Author–year — (Smith, 2023) in the text Smith, A., Jones, B. and Lee, C. (2023) 'A representative article title', European Heart Journal - Digital Health, 12(3), pp. 45–58.
Formats any DOI in the closest standard style — European Heart Journal - Digital Health has no published style definition, so this is an approximation. No sign-up. |
| Publishes research in | ECG Monitoring and Analysis Atrial Fibrillation Management and Outcomes Cardiovascular Function and Risk Factors Artificial Intelligence in Healthcare and Education Cardiac electrophysiology and arrhythmias |
| ISSN | 2634-3916 |
| Citation impact (2-yr) | 2.63 |
| h-index | 35 |
| i10-index | 181 |
| Total citations | 6,297 |
| Article processing charge | $3,018 |
| Open access | Yes |
| Top institutions publishing here | Erasmus University Rotterdam |
| Journal website | academic.oup.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Abstract Digital health technology (DHT) has the potential to revolutionize healthcare delivery but its uptake has been low in clinical and research settings. The factors that contribute to the limited adoption of DHT, particularly in cardiovascular settings, are unclear. The objective of this review was to determine the barriers and facilitators of DHT uptake from…
Aims: A majority of acute coronary syndromes (ACS) present without typical ST elevation. One-third of non-ST-elevation myocardial infarction (NSTEMI) patients have an acutely occluded culprit coronary artery [occlusion myocardial infarction (OMI)], leading to poor outcomes due to delayed identification and invasive management. In this study, we sought to develop a versatile artificial intelligence (AI) model…
Chat Generative Pre-trained Transformer (ChatGPT) is currently a trending topic worldwide triggering extensive debate about its predictive power, its potential uses, and its wider implications. Recent publications have demonstrated that ChatGPT can correctly answer questions from undergraduate exams such as the United States Medical Licensing Examination. We challenged it to answer questions from a more…
AIMS: Heart failure (HF) is a leading cause of death. Early intervention is the key to reduce HF-related morbidity and mortality. This study assesses the utility of electrocardiograms (ECGs) in HF risk prediction. METHODS AND RESULTS: Data from the baseline visits (1987-89) of the Atherosclerosis Risk in Communities (ARIC) study was used. Incident hospitalized HF…
Machine learning (ML) is a sub-field of artificial intelligence that uses computer algorithms to extract patterns from raw data, acquire knowledge without human input, and apply this knowledge for various tasks. Traditional statistical methods that classify or regress data have limited capacity to handle large datasets that have a low signal-to-noise ratio. In contrast to…
