ArticleAnatolian journal of cardiology2024
Artificial Intelligence-Based Clinical Decision Support Systems in Cardiovascular Diseases.
Article in Anatolian journal of cardiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.
What it found
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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
44 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Opportunities and Challenges of Cardiovascular Disease Risk Prediction for Primary Prevention Using Machine Learning and Electronic Health Records: A Systematic Review.Reviews in cardiovascular medicine · 2025Pooled it
- Operationalizing AI-Enabled Cardiovascular Biomarkers: A Clinician-Centered Framework for Validation, Governance, and Workflow Integration.JMIR cardio · 2026Article
- Beyond the Algorithm: Artificial Intelligence, Clinical Decision-Making, and the Moral Ecology of Care in Africa.Science and engineering ethics · 2026Article
- Molecular Basis of Adipose-Cardiac Crosstalk in Cardiovascular Diseases: From Mechanisms to Therapeutic Opportunities.Biomolecules · 2026Review
- From Automated ECG Interpretation to Multimodal Cardiovascular Intelligence: The Evolution of Artificial Intelligence in Cardiovascular Medicine.Medical sciences (Basel, Switzerland) · 2026Review
- Strategic Reform for the Non-Communicable Disease Crisis in Bangladesh: A Narrative Review of Policy Drivers and Systemic Solutions.Health science reports · 2026Article
- A narrative review on the use of artificial intelligence in cardiovascular medicine.Cardiovascular diagnosis and therapy · 2026Review
- Artificial intelligence construction: a review of the bridge between CT imaging features of lung ground-glass nodules adenocarcinoma and carcinogenic driver genes.Journal of cancer research and clinical oncology · 2026Review
- Artificial Intelligence in Cardiovascular Disease Prevention: Current Applications and Future Perspectives.Anatolian journal of cardiology · 2026Review
- A Supervised Learning Approach Electrocardiographic Model for Differentiating Outflow Tract Premature Ventricular Complex Origins: Comparative Analysis of Seven Established Algorithms.Anatolian journal of cardiology · 2026Article
- Multidisciplinary perspectives on artificial intelligence in aging research and education: evolving uses, ethics, and equity considerations in gerontology.The Gerontologist · 2026Article
- Perceived Potential and Challenges of Supporting Coronary Artery Disease Treatment Decisions With AI: Qualitative Study.JMIR cardio · 2026Article
- AI in the Hot Seat: Head-to-Head Comparison of Large Language Models and Cardiologists in Emergency Scenarios.Medical sciences (Basel, Switzerland) · 2026Article
- A hybrid deep learning and large language model framework for MACE risk prediction and evidence-based clinical recommendations.Frontiers in cardiovascular medicine · 2026Article
- Toward a National Health Digital and Data Architecture: Laying the Foundation for Digital Transformation: Commission on Investment Imperatives for a Healthy Nation.NAM perspectives · 2026Review
- Application of Telemedicine and Artificial Intelligence in Outpatient Cardiology Care: TeleAI-CVD Study (Design).Diagnostics (Basel, Switzerland) · 2026Article
- End-to-End Pipeline Integrating Local Small Language Models and Machine Learning for Data Extraction and Stroke Outcome Prediction in Emergency Department.Computational and structural biotechnology journal · 2026Article
- Multimodal Cardiovascular Risk Discrimination: Clinical, Biochemical, and Doppler Ultrasound Insights from a Contemporary Atherosclerotic Cardiovascular Disease Cohort.Anatolian journal of cardiology · 2025Article
- Medical Management of Coronary Artery Disease: An Update.The International journal of angiology : official publication of the International College of Angiology, Inc · 2025Review
- A predictive model for the treatment outcomes of patients with secondary mitral regurgitation based on machine learning and model interpretation.BMC medical informatics and decision making · 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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite all the advancements in science, medical knowledge, healthcare, and the healthcare industry, cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide. The main reasons are the inadequacy of preventive health services and delays in diagnosis due to the increasing population, the failure of physicians to apply guide-based treatments, the lack of continuous patient follow-up, and the low compliance of patients with doctors' recommendations. Artificial intelligence (AI)-based clinical decision support systems (CDSSs) are systems that support complex decision-making processes by using AI techniques such as data analysis, foresight, and optimization. Artificial intelligence-based CDSSs play an important role in patient care by providing more accurate and personalized information to healthcare professionals in risk assessment, diagnosis, treatment optimization, and monitoring and early warning of CVD. These are just some examples, and the use of AI for CVD decision support systems is rapidly evolving. However, for these systems to be fully reliable and effective, they need to be trained with accurate data and carefully evaluated by medical professionals.
Identifiers
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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.