ArticleEuropean heart journal2023
Artificial intelligence to enhance clinical value across the spectrum of cardiovascular healthcare.
Article in European heart journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
36 citing papers in PubMed.
- Consumer wearable devices for evaluation of heart rate control using digoxin versus beta-blockers: the RATE-AF randomized trial.Nature medicine · 2024Trial
- The AI-Driven Healthcare Value Framework-Rethinking Traditional Care Models in the Age of Automation.Healthcare (Basel, Switzerland) · 2026Article
- Personalised approach to hypertension treatment: protocol for the HYPERMARKER randomised controlled trial.BMJ open · 2026Article
- Molecular Mechanisms and Multi-Omics Integration in Heart Failure: From Pathophysiology to Precision Medicine.International journal of molecular sciences · 2026Review
- Clinical Artificial Intelligence Agents in Nephrology: From Prediction to Action Through Workflow-Native Intelligence-A Roadmap for Workflow-Integrated Care.Journal of clinical medicine · 2026Review
- Artificial intelligence-enhanced echocardiography in cardiovascular disease management.Nature reviews. Cardiology · 2026Review
- Advances in the Diagnosis and Management of High-Risk Cardiovascular Conditions: Biomarkers, Intracoronary Imaging, Artificial Intelligence, and Novel Anticoagulants.Journal of cardiovascular development and disease · 2026Review
- Risk prediction for long-term cardiovascular events in patients with concurrent hypertension, HFpEF, and unstable angina: a multicenter machine learning-assisted cohort study.Frontiers in endocrinology · 2026Article
- Precision medicine and personalized nursing in cardiovascular disease: clinical applications and frontier developments.Frontiers in cardiovascular medicine · 2026Review
- Atrial cardiomyopathy: From healthy atria to atrial failure. A clinical consensus statement of the Heart Failure Association of the ESC.European journal of heart failure · 2025Article
- Artificial Intelligence in the Diagnosis and Management of Atrial Fibrillation.Diagnostics (Basel, Switzerland) · 2025Review
- Contemporary and Emerging Therapeutics in Cardiovascular-Kidney-Metabolic (CKM) Syndrome: In Memory of Professor Akira Endo.Biomedicines · 2025Review
- Artificial Intelligence and Advanced Digital Health for Hypertension: Evolving Tools for Precision Cardiovascular Care.Medicina (Kaunas, Lithuania) · 2025Review
- Article
- Molecular Diagnostics in Heart Failure: From Biomarkers to Personalized Medicine.Diagnostics (Basel, Switzerland) · 2025Review
- Perception and Knowledge of Hospital Workers Toward Using Artificial Intelligence: A Descriptive Study.Health science reports · 2025Article
- Multimodal Visualization and Explainable Machine Learning-Driven Markers Enable Early Identification and Prognosis Prediction for Symptomatic Aortic Stenosis and Heart Failure With Preserved Ejection Fraction After Transcatheter Aortic Valve Replacement: Multicenter Cohort Study.Journal of medical Internet research · 2025Article
- Predicting Atrial Fibrillation Relapse Using Bayesian Networks: Explainable AI Approach.JMIR cardio · 2025Article
- Artificial intelligence in heart failure - a comprehensive literature review.Cardiology journal · 2025Review
- Optimization of Health Service Utilization Among Elderly People With Chronic Diseases in Rural Ethnic Minorities in Northwest Yunnan Using Graph Neural Networks.Blockchain in healthcare today · 2025Article
Corrections and comments
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Authors and funding
20 authors.
Funding
Abstract
Artificial intelligence (AI) is increasingly being utilized in healthcare. This article provides clinicians and researchers with a step-wise foundation for high-value AI that can be applied to a variety of different data modalities. The aim is to improve the transparency and application of AI methods, with the potential to benefit patients in routine cardiovascular care. Following a clear research hypothesis, an AI-based workflow begins with data selection and pre-processing prior to analysis, with the type of data (structured, semi-structured, or unstructured) determining what type of pre-processing steps and machine-learning algorithms are required. Algorithmic and data validation should be performed to ensure the robustness of the chosen methodology, followed by an objective evaluation of performance. Seven case studies are provided to highlight the wide variety of data modalities and clinical questions that can benefit from modern AI techniques, with a focus on applying them to cardiovascular disease management. Despite the growing use of AI, further education for healthcare workers, researchers, and the public are needed to aid understanding of how AI works and to close the existing gap in knowledge. In addition, issues regarding data access, sharing, and security must be addressed to ensure full engagement by patients and the public. The application of AI within healthcare provides an opportunity for clinicians to deliver a more personalized approach to medical care by accounting for confounders, interactions, and the rising prevalence of multi-morbidity.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.