SCIESCOPUSQ1
European Heart Journal - Digital Health
OXFORD UNIV PRESS, United Kingdom
European Heart Journal - Digital Health is an academic journal published by OXFORD UNIV PRESS (United Kingdom). Identifiers: eISSN 2634-3916. Indexed in SCIE, SCOPUS. Metrics: JIF 4.4, CiteScore 7.2, SJR 1.494, SNIP 1.30. Subject areas: CARDIAC & CARDIOVASCULAR SYSTEMS. tlooto lists 1,227 papers from this journal.
CiteScore
7.20
Scopus citation metric
SJR
1.494
SCImago rank
SNIP
1.30
Source normalized impact
Percentage rank
-
JIF percentile rank
Journal profile
- ISSN
- -
- eISSN
- 2634-3916
- Abbreviation
- EUR HEART J-DIGIT HL
- Publisher
- OXFORD UNIV PRESS
- Country
- United Kingdom
Web of Science categories
No Web of Science category data available.
Scopus ASJC categories
2705 Cardiology and Cardiovascular Medicine
Papers in this journal
Recent papers
- A digital solution to deliver remote training programs after centre-based cardiac rehabilitation for acutely decompensated heart failure: the PROMETEO study
2026
- Is there a possibility of changing lifestyle and physical activity in patients with chronic heart failure and type II diabetes? A telemedicine home-based experience
2026
- Machine learning for ventricular arrhythmia prediction: meta analysis
2026
- Enhancing pre-test probability models for suspected coronary artery disease using 12-lead electrocardiogram
2026
- AI-driven coronary stenosis detection versus IVUS reference standard
2026
Most cited papers
- Barriers and facilitators of the uptake of digital health technology in cardiovascular care: a systematic scoping review
2021 · 205 citations
- Machine learning based prediction models for cardiovascular disease risk using electronic health records data: systematic review and meta-analysis
2024 · 115 citations
- ChatGPT takes on the European Exam in Core Cardiology: an artificial intelligence success story?
2023 · 113 citations
- International evaluation of an artificial intelligence–powered electrocardiogram model detecting acute coronary occlusion myocardial infarction
2023 · 111 citations
- ECG-AI: electrocardiographic artificial intelligence model for prediction of heart failure
2021 · 91 citations