ReviewBiomedicines2025
The Heart of Transformation: Exploring Artificial Intelligence in Cardiovascular Disease.
Review in Biomedicines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Applications and challenges of biomarker-based predictive models in proactive health management.Frontiers in public health · 2025Pooled it
- Mapping the research landscape of artificial intelligence in heart failure: a bibliometric analysis.Annals of medicine and surgery (2012) · 2026Article
- Centroid Regression for Preoperative Risk Assessment of Acute Type A Aortic Dissection Based on Multivariate Clinical Data.Journal of clinical medicine · 2026Article
- Artificial intelligence in public health-challenges and opportunities.European journal of clinical nutrition · 2026Review
- Explainable artificial intelligence in electrocardiography: A systematic review.Biomedical signal processing and control · 2026Article
- Artificial Intelligence and Machine Learning Applications in Fibromuscular Dysplasia: Transforming Diagnosis, Risk Stratification, and Clinical Decision-Making.Journal of cardiovascular translational research · 2026Review
- Special Issue "Cellular and Molecular Progression of Cardiovascular Diseases".International journal of molecular sciences · 2026Article
- Radiomics of Pericoronary Adipose Tissue and CT-FFR to Predict Major Adverse Cardiovascular Events in Patients with T2DM Complicated by CAD.Journal of cardiovascular translational research · 2026Article
- Enhancing clinically cardiovascular machine learning model for risk prediction via sample augmentation.Frontiers in medicine · 2026Article
- A comparative performance analysis of ensemble learning and regularized neural networks in cardiovascular risk prediction.Frontiers in medical technology · 2026Article
- Evaluation of coronary heart disease risk prediction based on simple physical examination parameters by machine learning model: a retrospective cohort model development and validation study.Frontiers in cardiovascular medicine · 2026Article
- Data augmentation alters feature importance in XGBoost for CVD prediction.Scientific reports · 2025Article
- Artificial Intelligence in Drug-Coated Cardiovascular Devices: A Narrative Review.Reviews in cardiovascular medicine · 2025Review
- Pre-trained Artificial Intelligence Models in the Prediction and Classification of Atherosclerotic Cardiovascular Disease.The Eurasian journal of medicine · 2025Article
- A Machine Learning Approach to Predict Successful Trans-Ventricular Off-Pump Micro-Invasive Mitral Valve Repair.Journal of clinical medicine · 2025Article
- Longitudinal Myocardial Deformation as an Emerging Biomarker for Post-Traumatic Cardiac Dysfunction.Life (Basel, Switzerland) · 2025Review
- Right Ventricular Dynamics in Tricuspid Regurgitation: Insights into Reverse Remodeling and Outcome Prediction Post Transcatheter Valve Intervention.International journal of molecular sciences · 2025Review
- Determinants of artificial intelligence electrocardiogram-derived age and its association with cardiovascular events and mortality: a systematic review and meta-analysis.NPJ digital medicine · 2025Article
- Cognitive alignment in cardiovascular AI: designing predictive models that think with, not just for, clinicians.Frontiers in cardiovascular medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The application of artificial intelligence (AI) and machine learning (ML) in medicine and healthcare has been extensively explored across various areas. AI and ML can revolutionize cardiovascular disease management by significantly enhancing diagnostic accuracy, disease prediction, workflow optimization, and resource utilization. This review summarizes current advancements in AI and ML concerning cardiovascular disease, including their clinical investigation and use in primary cardiac imaging techniques, common cardiovascular disease categories, clinical research, patient care, and outcome prediction. We analyze and discuss commonly used AI and ML models, algorithms, and methodologies, highlighting their roles in improving clinical outcomes while addressing current limitations and future clinical applications. Furthermore, this review emphasizes the transformative potential of AI and ML in cardiovascular practice by improving clinical decision making, reducing human error, enhancing patient monitoring and support, and creating more efficient healthcare workflows for complex cardiovascular conditions.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.