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Manuscript Auditing →01Impact factor
Impact factor of Frontiers in Cardiovascular Medicine (2026)
The impact factor shown here is the 2-year mean citedness: citations received in a year by the papers Frontiers in Cardiovascular Medicine published in the two previous years, divided by the number of those papers. That is the same formula as the Journal Impact Factor, applied to the open citation data of OpenAlex. The journal is listed in JCR 2024, so it also has an official Journal Impact Factor published by Clarivate, which can differ because it counts citations from Web of Science journals only.
Rank in its subject categories
- Q2Cardiac & Cardiovascular Systemrank 78 of 250 journals
Quartiles here rank journals of the same Web of Science category by 2-year citedness; they are not the official JCR quartiles.
Citations and papers per year
Open access (listed in DOAJ); article processing charge listed at about US$3,801.
02Indexing
Indexing of Frontiers in Cardiovascular Medicine
- ISSN
- 2297-055X
- Publisher
- Frontiers Media SA
- Country
- Switzerland
- Language
- English
- Scopus source type
- Journal
- Web of Science categories
- Cardiac & Cardiovascular System
From the indexing lists used on ScholarsColab, updated 1 March 2026. Indexing can change: confirm on the Web of Science Master Journal List or the Scopus source list before submitting. Official Journal Impact Factors and JCR quartiles are published by Clarivate; the impact factor and quartile on this page are calculated from OpenAlex open data (see how the impact factor works).
03What it publishes
What Frontiers in Cardiovascular Medicine publishes: real papers
Words that appear most often in the titles of the papers published here that we track. Choose one to see those papers:
04Published papers
Papers published in Frontiers in Cardiovascular Medicine
Papers from the publication records ScholarsColab tracks, with their year and citations. Author names are not shown.
- Construction of a competitive endogenous RNA network and identification of potential regulatory axes in hypertrophic cardiomyopathy20260 citations
- Saphenous vein graft and nitric oxide: strategies to prevent graft failure and enhance patency in coronary artery bypass grafting20260 citations
- Case Report: Upper extremity deep vein thrombosis revealing an occult invasive ductal breast carcinoma20260 citations
- CT-based visualization of aortic valve morphology: from 3D energy-integrating CT to 4D photon counting CT20260 citations
- Multimodal evidence chain of iron overload, inflammation, and dysfunction: an integrated predictive model of early cardiac injury in pediatric transfusion-dependent β …20260 citations
- Rescue bare-metal stent placement restoring multilevel perfusion in acute type B aortic dissection: a case report20260 citations
- Federated learning for cardiovascular disease prediction: a systematic review of clinical applications, validation, and translation readiness20260 citations
- Machine learning approaches for risk prediction in aortic dissection: a systematic review and meta-analysis20260 citations
- Artificial intelligence optimizes immune rejection prediction and management in heart transplantation: a structured narrative review20260 citations
- Transient cortical blindness following coronary angiography: a case report20260 citations
- Relationship between body roundness index and mortality rates and life expectancy in populations with metabolic syndrome20260 citations
- Performance of image-based deep learning models for aortic dissection segmentation and diagnosis: a systematic review and meta-analysis20260 citations
- Machine learning-based early warning system for hemodynamic deterioration in cardiovascular ICU patients: a bidirectional cross-validation study20260 citations
- Artificial intelligence in cardio-oncology: decoding mechanisms, predicting toxicity, and personalizing cancer therapy20260 citations
- A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology20250 citations
- The potential role of stellate ganglion block in impacting the central and peripheral systems: a narrative review20250 citations
- Identification and validation of key biomarkers of the glycolysis-ketone body metabolism in heart failure based on multi-omics and machine learning20250 citations
- Application-based remote interstage home monitoring for infants with shunt-or duct-dependent pulmonary perfusion20250 citations
- Machine learning algorithms for predicting atrial fibrillation using single-lead data derived from 12-lead ECGs20250 citations
- An explainable machine learning model for predicting chronic coronary disease and identifying valuable text features20250 citations
- Core and bridging symptoms in patients with atrial fibrillation: a network analysis20250 citations
- Cor Triatriatum: an uncommon congenital anomaly-the experience of a tertiary care center in a developing country20250 citations
- Machine learning algorithms to predict heart failure with preserved ejection fraction among patients with premature myocardial infarction20250 citations
- A clinical prediction model for blood pressure changes after renal denervation in patients with resistant hypertension20250 citations
- Machine learning-based prediction model for recurrence after radiofrequency catheter ablation in patients with atrial fibrillation20250 citations
- … of percutaneous coronary intervention with different guidance modalities in patients with coronary artery lesions: a network meta-analysis and systematic review20250 citations
- Association of SMuRFs with cardiovascular risk factors, disease burden, and pharmacological management in Middle Eastern patients with ASCVD and a family …20250 citations
- Prevalence and determinants of multidimensional frailty in hospitalized older adults with coronary heart disease: a LASSO regression analysis20250 citations
- Electrocardiography-based artificial intelligence predicts the upcoming future of heart failure with mildly reduced ejection fraction20250 citations
- The role of the PD-1/PD-L1 immune checkpoint pathway in myocardial infarction: a review from pathophysiological mechanisms to therapeutic strategies20250 citations
- Identification of arachidonic acid metabolism-related diagnostic markers in heart failure based on bioinformatics analysis and machine learning20250 citations
- CLU, FOS, and CXCL8 as diagnostic biomarkers for heart failure progression post-acute myocardial infarction: an integrated RNA-Seq and multi-machine learning …20250 citations
- The λ pattern on time-RR interval scatter plot of neonatal ambulatory ECG: a marker of transient bradycardia20250 citations
- Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning20250 citations
- Predicting the rapid progression of coronary artery lesions in patients with acute coronary syndrome based on machine learning20250 citations
- Contrastive learning with transformer for adverse endpoint prediction in patients on DAPT post-coronary stent implantation20250 citations
- Photon counting CT technology in cardiovascular imaging20250 citations
- Global burden of hypertensive heart disease attributable to high body mass index from 1990 to 2021: a multidimensional analysis and public health response20250 citations
- Herb pair of Astragali Radix-Descurainiae Semen attenuate heart failure through the myosin VI-Tom1 complex mediated autophagy20250 citations
- Data source and utilization of artificial intelligence technologies in vascular surgery—a scoping review20250 citations
- Effect of a fast-track nursing pathway for emergency percutaneous coronary intervention on clinical outcomes in patients with acute myocardial infarction20250 citations
- Targeting inhibition of the inflammatory response: advances in the treatment of myocardial fibrosis with natural medicine and active ingredients20250 citations
- The role of artificial intelligence technologies in revolutionizing and aiding cardiovascular medicine20250 citations
- Mapping the research landscape of artificial hearts: identifying hotspots and frontiers through bibliometric analysis20250 citations
- Nutrient restriction protects against valve interstitial cell calcification by upregulating ubiquitin mediated proteolysis20250 citations
- Artificial intelligence enabled mobile health technologies in arrhythmias-an opinion article on recent findings20250 citations
- Nanoparticle-based drug delivery systems targeting inflammatory immune mechanisms in acute myocardial infarction: current advances and perspectives20250 citations
- Global ischemic heart disease burden attributable to kidney dysfunction from 1990 to 2021 and projections to 2050: results from the global burden of disease study …20250 citations
- A multi-center, randomized, double-blind, placebo-controlled trial to evaluate the efficacy and safety of Fuzheng Yangxin Granule in treating heart failure with …20250 citations
- Disulfidptosis-related gene in acute myocardial infarction and its diagnostic value and functions based on bioinformatics analysis and machine learning20250 citations
- Analysis and validation of characteristic genes in RNA sequencing datasets from heart failure patients based on multiple algorithms20250 citations
- Effects of singing on vascular health in older adults with coronary artery disease: A randomized, crossover trial20250 citations
- From patterns to prognosis: machine learning–derived clusters in advanced heart failure20250 citations
- Immunosuppressant adherence after heart transplantation: a review on detection, prevention, and intervention strategies in a multidisciplinary20250 citations
- Artificial intelligence in atrial fibrillation: emerging applications, research directions and ethical considerations20250 citations
- Comparison of the right–left ventricular stroke volume difference evaluated by echocardiography in patients with chronic heart failure complicated with cardiogenic …20250 citations
- Role of peri-deployment right ventricular paced-ECG in left bundle area pacing20250 citations
- Integrating the BAN-ADHF diuretic resistance score into same day emergency care centres for heart failure management: a conceptual framework20250 citations
- ECG-XPLAIM: eXPlainable Locally-adaptive Artificial Intelligence Model for arrhythmia detection from large-scale electrocardiogram data20250 citations
- Pathways of influence on health-promoting lifestyles in older adults with coronary heart disease: a cross-sectional study20250 citations
- AI-driven decision making for intravascular device selection in aortic disease. Current insights and prospects20250 citations
- Development and interpretation of a machine learning predictive model for early cognitive impairment in hypertension associated with environmental factors20250 citations
- Point-of-care ultrasound in the evaluation of STEMI patients20250 citations
- Exploring the effects of real-time online cardiac telerehabilitation using wearable devices compared to gym-based cardiac exercise in people with a recent myocardial …20240 citations
- Christopher J. Hatch1, Sebastian D. Piombo2, Jennifer S. Fang3, Johannes S. Gach4, Makena L. Ewald3, William K. Van Trigt3, Brian G. Coon5, 6, Jay M …20240 citations
- Navigating the AI frontiers in cardiovascular research: a bibliometric exploration and topic modeling20240 citations
- A novel hybrid machine learning model for auxiliary diagnosing myocardial ischemia20240 citations
- Artificial intelligence applied in cardiovascular disease: a bibliometric and visual analysis20240 citations
- Monitoring and evaluation of hypotension in the extremely preterm20240 citations
- Right anterior thoracotomy vs. upper hemisternotomy for aortic valve replacement with Perceval S: is there a difference?20240 citations
- Explainable coronary artery disease prediction model based on AutoGluon from AutoML framework20240 citations
- Wearable Patch ECG monitors and transesophageal electrophysiological study for diagnosing palpitations of unknown origin20240 citations
- Convolutional neural network (CNN)-enabled electrocardiogram (ECG) analysis: a comparison between standard twelve-lead and single-lead setups20240 citations
- Machine learning models to predict 30-day mortality for critical patients with myocardial infarction: a retrospective analysis from MIMIC-IV database20240 citations
- Association between deep neural network-derived electrocardiographic-age and incident stroke20240 citations
- Study on the related factors of TCM constitution and hemodynamics in patients with coronary heart disease20240 citations
- Artificial intelligence based real-time prediction of imminent heart failure hospitalisation in patients undergoing non-invasive telemedicine20240 citations
- Multifractal analysis of heart rate variability in pregnancy during sleep20240 citations
- A Lifelike guided journey through the pathophysiology of pulmonary hypertension—from measured metabolites to the mechanism of action of drugs20240 citations
- Estimation of aortic stiffness by finger photoplethysmography using enhanced pulse wave analysis and machine learning20240 citations
- Loss of protein phosphatase 2A regulatory subunit PPP2R5A is associated with increased incidence of stress-induced proarrhythmia20240 citations
- CircRNA-mediated regulation of cardiovascular disease20240 citations
- Tongue color parameters in predicting the degree of coronary stenosis: a retrospective cohort study of 282 patients with coronary angiography20240 citations
- Temperature management in acute type A aortic dissection treatment: deep vs. moderate hypothermic circulatory arrest. Is colder better?20240 citations
- Cardiovascular disease prevention in the workplace20240 citations
- A novel method of swin transformer with time-frequency characteristics for ECG-based arrhythmia detection20240 citations
- Performance of federated learning-based models in the Dutch TAVI population was comparable to central strategies and outperformed local strategies20240 citations
- Causal associations between chronic heart failure and the cerebral cortex: results from Mendelian randomization study and integrated bioinformatics analysis20240 citations
- A novel approach for denoising electrocardiogram signals to detect cardiovascular diseases using an efficient hybrid scheme20240 citations
- Change in left ventricular function and outcomes following high-risk percutaneous coronary intervention with Impella-guided hemodynamic support20240 citations
- Linking preoperative and early intensive care unit data for prolonged intubation prediction20240 citations
- Construction and validation of risk prediction models for pulmonary embolism in hospitalized patients based on different machine learning methods20240 citations
- Sex-related differences in incidence, phenotype and risk of sudden cardiac death in inherited arrhythmia syndromes20230 citations
- Deep learning assessment of left ventricular hypertrophy based on electrocardiogram20230 citations
- Atrial fibrillation: primary prevention, secondary prevention, and prevention of thromboembolic complications: part 120230 citations
- Impact of severe secondary tricuspid regurgitation on rest and exercise hemodynamics of patients with heart failure and a preserved left ventricular ejection fraction20230 citations
- Ferroptosis, necroptosis and cuproptosis: Novel forms of regulated cell death in diabetic cardiomyopathy20230 citations
- Tricuspid regurgitation, right ventricular function, and renal congestion: a cardiorenal triangle20230 citations
- Stroke risk study based on deep learning-based magnetic resonance imaging carotid plaque automatic segmentation algorithm20230 citations
- Machine learning-based prediction of acute mortality in emergency department patients using twelve-lead electrocardiogram20230 citations
- Identification of risk factors for infection after mitral valve surgery through machine learning approaches20230 citations
- Barriers and opportunities: Intercellular mitochondrial transfer for cardiac protection—Delivery by extracellular vesicles20230 citations
- Comparison of machine learning and logistic regression as predictive models for adverse maternal and neonatal outcomes of preeclampsia: A retrospective study20230 citations
- Remote monitoring of implantable loop recorders reduces time to diagnosis in patients with unexplained syncope: a multicenter propensity score-matched study20230 citations
- Artificial intelligence-assisted remote detection of ST-elevation myocardial infarction using a mini-12-lead electrocardiogram device in prehospital ambulance care20230 citations
- Remote monitoring titration clinic to implement guideline-directed therapy for heart failure patients with reduced ejection fraction: a pilot quality-improvement …20230 citations
- Deep learning-based end-to-end automated stenosis classification and localization on catheter coronary angiography20230 citations
- The patient perspective on remote monitoring of implantable cardiac devices20230 citations
- Radiomics signature of epicardial adipose tissue for predicting postoperative atrial fibrillation after pulmonary endarterectomy20230 citations
- Strategies in activating lymphatic system on symptom distress and health-related quality of life in patients with heart failure: secondary analysis of a pilot randomized …20230 citations
- Nano drugs delivery system: A novel promise for the treatment of atrial fibrillation20230 citations
- CARDIAN: a novel computational approach for real-time end-diastolic frame detection in intravascular ultrasound using bidirectional attention networks20230 citations
- In-stent restenosis in acute coronary syndrome—a classic and a machine learning approach20230 citations
- PlaqView 2.0: A comprehensive web portal for cardiovascular single-cell genomics20230 citations
- Noninvasive evaluation of pulmonary hypertension using the second heart sound parameters collected by a mobile cardiac acoustic monitoring system20230 citations
- Bioinformatics analysis of lncRNA-related ceRNA networks in the peripheral blood lymphocytes of Kazakh patients with essential hypertension in Xinjiang20230 citations
- Research topic for frontiers in cardiovascular medicine: non-invasive sensing and imaging techniques for cardiometabolic diseases20230 citations
- Economic analysis of remote monitoring in patients with implantable cardioverter defibrillators or cardiac resynchronization therapy defibrillators in the Trento area …20230 citations
- Identification of energy metabolism-related biomarkers for risk prediction of heart failure patients using random forest algorithm20230 citations
- Data driven and model based computational futures in cardiovascular practice20230 citations
- Contactless multiscale measurement of cardiac motion using biomedical radar sensor20230 citations
- Real-time heart rate variability according to ambulatory glucose profile in patients with diabetes mellitus20230 citations
- Artificial intelligence-estimated biological heart age using a 12-lead electrocardiogram predicts mortality and cardiovascular outcomes20230 citations
- Predicting in-hospital all-cause mortality in heart failure using machine learning20230 citations
- Advances and challenges in remote monitoring of patients with heart failure20230 citations
- Identification of hsa_circ_0001445 of a novel circRNA-miRNA-mRNA regulatory network as potential biomarker for coronary heart disease20230 citations
- Modified Linggui Zhugan Decoction protects against ventricular remodeling through ameliorating mitochondrial damage in post-myocardial infarction rats20230 citations
- Circular RNAs in vascular diseases20230 citations
- Clinician's guide to trustworthy and responsible artificial intelligence in cardiovascular imaging20230 citations
- The NMDA receptor regulates integrin activation, ATP release and arterial thrombosis through store-operated Ca2+ entry in platelets20230 citations
- Modelling blood flow in patients with heart valve disease using deep learning: a computationally efficient method to expand diagnostic capabilities in clinical routine20230 citations
- Towards realistic privacy-preserving deep learning over encrypted medical data20230 citations
- Hybrid model of CT-fractional flow reserve, pericoronary fat attenuation index and radiomics for predicting the progression of WMH: a dual-center pilot study20230 citations
- Adversarial-based latent space alignment network for left atrial appendage segmentation in transesophageal echocardiography images20230 citations
- Incremental predictive utility of a radiomics signature in a nomogram for the recurrence of atrial fibrillation20230 citations
- Applications of machine learning in familial hypercholesterolemia20230 citations
- Subject-specific factors affecting particle residence time distribution of left atrial appendage in atrial fibrillation: A computational model-based study20230 citations
- Lower ventricular and atrial strain in patients who recovered from COVID-19 assessed by cardiovascular magnetic resonance feature tracking20230 citations
- Artificial intelligence in coronary computed tomography angiography: Demands and solutions from a clinical perspective20230 citations
- Large animal models for cardiac remuscularization studies: a methodological review20230 citations
- Machine learning algorithms to predict major bleeding after isolated coronary artery bypass grafting20220 citations
- Remote cardiac rhythm monitoring in the era of smart wearables: present assets and future perspectives20220 citations
- Pursuing connectivity in cardio-oncology care—the future of telemedicine and artificial intelligence in providing equity and access to rural communities20220 citations
- Cachet-cadb: A contextualized ambulatory electrocardiography arrhythmia dataset20220 citations
- Electrocardiogram-based heart age estimation by a deep learning model provides more information on the incidence of cardiovascular disorders20220 citations
- Real-world and regulatory perspectives of artificial intelligence in cardiovascular imaging20220 citations
- Augmented detection of septal defects using advanced optical coherence tomography network-processed phonocardiogram20220 citations
- Optimal time of collapse to return of spontaneous circulation to apply targeted temperature management for cardiac arrest: a Bayesian network meta-analysis20220 citations
- Exosomes derived from pericardial adipose tissues attenuate cardiac remodeling following myocardial infarction by Adipsin-regulated iron homeostasis20220 citations
- Hypoglycemia-Exacerbated mitochondrial connexin 43 accumulation aggravates cardiac dysfunction in diabetic cardiomyopathy20220 citations
- Interpretable machine learning for 28-day all-cause in-hospital mortality prediction in critically ill patients with heart failure combined with hypertension: a retrospective …20220 citations
- Machine learning-based prediction of the post-thrombotic syndrome: model development and validation study20220 citations
- Case report: The impact of percutaneous atrial septal defect closure in pulmonary hypertension with co-existing cor triatriatum sinister and multiple cardiac …20220 citations
- Enhanced angiogenesis by 11βHSD1 blockage is insufficient to improve reperfusion following hindlimb ischaemia20220 citations
- Clinical implications of heart rate control in heart failure with atrial fibrillation: Multi-Center Prospective Observation Registry (CODE-AF Registry)20220 citations
- A collaborative approach for the development and application of machine learning solutions for CMR-based cardiac disease classification20220 citations
- A phenotype and genotype case report of a neonate with congenital bilateral coronary artery fistulas and multiple collateral arteries20220 citations
- A cardiovascular disease prediction model based on routine physical examination indicators using machine learning methods: a cohort study20220 citations
- Early prediction of clinical scores for left ventricular reverse remodeling using extreme gradient random forest, boosting, and logistic regression algorithm …20220 citations
- Feasibility of an automatic ultrasonographic image acquisition system associated with an artificial intelligence algorithm for real-time monitoring of cardiac motion …20220 citations
- Machine learning patient-specific prediction of heart failure hospitalization using cardiac MRI-based phenotype and electronic health information20220 citations
- Induced pluripotent stem cell-derived smooth muscle cells to study cardiovascular calcification20220 citations
- A stable and quantitative method for dimensionality reduction of aortic centerline20220 citations
- WSSNet: aortic wall shear stress estimation using deep learning on 4D flow MRI20220 citations
- Deep learning networks accurately detect ST-segment elevation myocardial infarction and culprit vessel20220 citations
- CaMKII-δ9 induces cardiomyocyte death to promote cardiomyopathy and heart failure20220 citations
- Increasing adiposity is associated with QTc interval prolongation and increased ventricular arrhythmic risk in the context of metabolic dysfunction: results from the UK …20220 citations
- Optimal lesion size index for pulmonary vein isolation in high-power radiofrequency catheter ablation of atrial fibrillation20220 citations
- Machine learning assisted reflectance spectral characterisation of coronary thrombi correlates with microvascular injury in patients with ST-segment elevation acute …20220 citations
- Estimation of heart rate variability parameters by machine learning approaches applied to facial infrared thermal imaging20220 citations
- IL-6/STAT3 signaling promotes cardiac dysfunction by upregulating FUNDC1-dependent mitochondria-associated endoplasmic reticulum membranes formation in …20220 citations
- Unique angiogenesis from cardiac arterioles during pericardial adhesion formation20220 citations
- Fairness in cardiac magnetic resonance imaging: assessing sex and racial bias in deep learning-based segmentation20220 citations
- Efficacy of INtensive Treatment vs. Standard Treatment of COmpound DanshEn Dripping Pills in Refractory Angina Patients With Incomplete Revascularization …20220 citations
- Epidemiology of atrial fibrillation and related myocardial ischemia or arrhythmia events in Chinese community population in 201920220 citations
- Epidemiology of congenital heart disease in Jinan, China from 2005 to 2020: a time trend analysis20220 citations
- Late plasma exosome microRNA-21-5p depicts magnitude of reverse ventricular remodeling after early surgical repair of primary mitral valve regurgitation20220 citations
- Outcomes of one-stage surgical repair for Berry syndrome in neonates20220 citations
- GSVMA: a genetic support vector machine ANOVA method for CAD diagnosis20220 citations
- Identification of key programmed cell death-related genes and immune infiltration in extracorporeal membrane oxygenation treatment for acute myocardial infarction …20220 citations
- Quantitative analysis of venous outflow with photo-plethysmography in patients with suspected thoracic outlet syndrome20220 citations
- A self-supervised deep learning reconstruction for shortening the breathhold and acquisition window in cardiac magnetic resonance fingerprinting20220 citations
- Epigenetic mechanism and therapeutic implications of atrial fibrillation20220 citations
- Application of postoperative remote follow-up of CIED based on the 5G cloud technology support platform in areas with underdeveloped medical resources20220 citations
- A sensorless modular multiobjective control algorithm for left ventricular assist devices: A clinical pilot study20220 citations
- Use of multi-modal data and machine learning to improve cardiovascular disease care20220 citations
- Artificial intelligence in cardiac MRI: is clinical adoption forthcoming?20220 citations
- Pocket CLARITY enables distortion-mitigated cardiac microstructural tissue characterization of large-scale specimens20220 citations
- ECG-based techniques to optimize peripherally inserted central catheters: rationale for tip positioning and practical use20220 citations
- Artificial intelligence in cardiology: Hope for the future and power for the present20220 citations
- Using innovative machine learning methods to screen and identify predictors of congenital heart diseases20220 citations
- Case report: ambient sensor signals as digital biomarkers for early signs of heart failure decompensation20210 citations
- Implementing machine learning in interventional cardiology: the benefits are worth the trouble20210 citations
- Local and distributed machine learning for inter-hospital data utilization: an application for TAVI outcome prediction20210 citations
- Machine learning algorithms to detect sex in myocardial perfusion imaging20210 citations
- MOCOnet: robust motion correction of cardiovascular magnetic resonance T1 mapping using convolutional neural networks20210 citations
- Similarities and differences between HFmrEF and HFpEF20210 citations
- Case report: isolate congenital coronary artery fistula with giant artery aneurysm in a neonate20210 citations
- Case report: Prenatal diagnosis and treatment of fetal autoimmune-associated first-degree atrioventricular block: First report from China20210 citations
- The Outcomes of Total Anomalous Pulmonary Venous Connection in Neonates− 10-Year Experience at a Single Center20210 citations
- Cardiac 18F-FDG Positron Emission Tomography: An Accurate Tool to Monitor In vivo Metabolic and Functional Alterations in Murine Myocardial Infarction20210 citations
- Characterization of flow dynamics in the pulmonary bifurcation of patients with repaired tetralogy of Fallot: a computational approach20210 citations
- A proposal for a data-driven approach to the influence of music on heart dynamics20210 citations
- Integrated Pharmacogenetics Analysis of the Three Fangjis Decoctions for Treating Arrhythmias Based on Molecular Network Patterns20210 citations
- Endovascular treatment of pelvic congestion syndrome: visual analog scale follow-up20210 citations
- Application of machine learning in diagnosis of COVID-19 through X-ray and CT images: a scoping review20210 citations
- Automatic segmentation and cardiac mechanics analysis of evolving zebrafish using deep learning20210 citations
- The role of METTL3-mediated N6-methyladenosine (m6A) of JPH2 mRNA in cyclophosphamide-induced cardiotoxicity20210 citations
- Automated left ventricle ischemic scar detection in CT using deep neural networks20210 citations
- Aortic dissection auxiliary diagnosis model and applied research based on ensemble learning20210 citations
- Exercise Training Stabilizes RyR2-Dependent Ca2+ Release in Post-infarction Heart Failure20210 citations
- Symmetric projection attractor reconstruction: sex differences in the ECG20210 citations
- Leveraging innovation, education, and technology for prevention and health equity: Proceedings from the cardiology oncology innovation ThinkTank 202120210 citations
- Detection of left atrial enlargement using a convolutional neural network-enabled electrocardiogram20200 citations
- Progressive reinvention or destination lost? Half a century of cardiovascular tissue engineering20200 citations
- Safety and efficacy of adding dapagliflozin to furosemide in type 2 diabetic patients with decompensated heart failure and reduced ejection fraction20200 citations
- Machine learning approaches for myocardial motion and deformation analysis20200 citations
- Changes in continuous, long-term heart rate variability and individualized physiological responses to wellness and vacation interventions using a wearable sensor20200 citations
- Standardization of Human Calcific Aortic Valve Disease in vitro Modeling Reveals Passage-Dependent Calcification20190 citations
- Artificial intelligence will transform cardiac imaging—opportunities and challenges20190 citations
- Staff recall travel time for ST elevation myocardial infarction impacted by traffic congestion and distance: a digitally integrated map software study20180 citations
05Reviewer comments
Reviewer comments and rejection reasons for Frontiers in Cardiovascular Medicine
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06Similar journals
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07Journal Finder
Find the right journal for your paper
Is Frontiers in Cardiovascular Medicine right for your paper? Compare journals
Paste your title, keywords or abstract. We match it against 156,435 published journal papers, by ScholarsColab mentors and other researchers, and show where the closest work appeared, with each journal’s indexing (SCIE, SSCI, AHCI, ESCI, Scopus, JCR 2024).
How it works: no AI or language model is used. Your words are matched against the titles of real published journal papers, by our mentors and by other researchers (shown without names); journals are ranked by how many closely matching papers they published. Indexing comes from the SCIE, SSCI, AHCI, ESCI, Scopus and JCR 2024 lists, matched by journal name; “not found in our indexing lists” does not prove a journal is unindexed. Always check a journal’s scope and current indexing before submitting.
08Questions
Frequently asked questions
What is the impact factor of Frontiers in Cardiovascular Medicine?
Based on OpenAlex citation data (October 2026), the 2-year impact factor of Frontiers in Cardiovascular Medicine is 2.46: papers it published in the two previous years were cited 2.46 times on average in a year. The journal is listed in JCR 2024, so Clarivate also publishes an official Journal Impact Factor, which can differ.
What is the h-index of Frontiers in Cardiovascular Medicine?
The h-index of Frontiers in Cardiovascular Medicine is 116 (OpenAlex, October 2026): 116 of its papers have each been cited at least 116 times. Its i10-index is 4,921.
What is the APC of Frontiers in Cardiovascular Medicine?
OpenAlex lists an article processing charge (APC) of about US$3,801 for Frontiers in Cardiovascular Medicine, an open access journal (data from October 2026). APCs change and can differ by article type, country or discounts, so confirm the current charge on the journal’s website before submitting.
Is Frontiers in Cardiovascular Medicine a Q2 journal?
By 2-year citedness, Frontiers in Cardiovascular Medicine ranks 78 of 250 journals in Cardiac & Cardiovascular System, which places it in Q2 of that Web of Science category. This ranking is calculated by ScholarsColab from OpenAlex data; the official JCR quartile can differ.
Is Frontiers in Cardiovascular Medicine indexed in Scopus?
Yes. Frontiers in Cardiovascular Medicine appears in the Scopus list, according to the indexing lists used on ScholarsColab (updated 1 March 2026). Always confirm the current status on the official list before submitting.
Is Frontiers in Cardiovascular Medicine an SCIE journal?
Yes. Frontiers in Cardiovascular Medicine is listed in the Science Citation Index Expanded (SCIE), according to the indexing lists used on ScholarsColab (updated 1 March 2026). Always confirm the current status on the official list before submitting.
Is Frontiers in Cardiovascular Medicine in Journal Citation Reports (JCR)?
Yes. Frontiers in Cardiovascular Medicine is listed in JCR 2024, so it has a Journal Impact Factor. For the current impact factor and quartile, check Journal Citation Reports.
What topics does Frontiers in Cardiovascular Medicine publish?
The papers published in Frontiers in Cardiovascular Medicine that we track most often mention learning, heart, machine, patient, failure, cardiac. Check the journal’s aims and scope for its full coverage.
How many papers published in Frontiers in Cardiovascular Medicine does ScholarsColab track?
We track 221 papers published in Frontiers in Cardiovascular Medicine between 2018 and 2026, cited 0 times in total, with a median of 0 citations per paper.
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