ReviewAnatolian journal of cardiology2025
Artificial Intelligence in Cardiology: General Perspectives and Focus on Interventional Cardiology.
Review in Anatolian journal of cardiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Unimodal to multimodal: a systematic review of predictive machine learning models for valvular heart diseases.Frontiers in cardiovascular medicine · 2026Pooled it
- Beyond Traditional Risk Scores: Artificial Intelligence in Coronary Plaque Characterization and Personalized Atherosclerosis Management.Journal of cardiovascular development and disease · 2026Review
- A Survey on Perspectives Toward Artificial Intelligence Among Italian Interventional Cardiologists.Journal of clinical medicine · 2026Article
- Post-MI Remodeling Mechanics of Left Ventricle: Microstructure-Informed Models, Identifiability, and Uncertainty for Patient-Specific Prediction.Bioengineering (Basel, Switzerland) · 2026Review
- Explainable and Trustworthy Artificial Intelligence in Cardiology: A Narrative Review of Clinical Applications, Operational Integration, and Future Directions.Journal of clinical medicine · 2026Review
- A leap into the future: excluding the ischaemic origin of chest pain through artificial intelligence.European heart journal supplements : journal of the European Society of Cardiology · 2026Article
- Artificial Intelligence in Cardiovascular Disease Prevention: Current Applications and Future Perspectives.Anatolian journal of cardiology · 2026Review
- The role of artificial intelligence in early detection and risk prediction of ischemic heart disease.Annals of medicine and surgery (2012) · 2026Review
- Synthetic artificial intelligence in cardiology: from generative models to clinical applications.European heart journal open · 2026Review
- Digital Medicine in the Management of Heart Failure: From Reactive Care to Predictive, Pathophysiology-Driven Strategies.Healthcare (Basel, Switzerland) · 2026Review
- Managing Arterial Hypertension in Chronic Renal Failure: Myths, Mechanisms, and Therapeutic Realities.Journal of clinical medicine · 2026Review
- Psychiatry and artificial intelligence: A need for informed engagement.The South African journal of psychiatry : SAJP : the journal of the Society of Psychiatrists of South Africa · 2026Article
- Application of Telemedicine and Artificial Intelligence in Outpatient Cardiology Care: TeleAI-CVD Study (Design).Diagnostics (Basel, Switzerland) · 2026Article
- Toward Artificial Intelligence in Oncology and Cardiology: A Narrative Review of Systems, Challenges, and Opportunities.Journal of clinical medicine · 2025Article
- Advanced Computer Simulation Based on Cardiac Imaging in Planning of Structural Heart Disease Interventions.Journal of clinical medicine · 2025Review
- Reperfusion injury in STEMI: a double-edged sword.The Egyptian heart journal : (EHJ) : official bulletin of the Egyptian Society of Cardiology · 2025Review
- Digital Cardiovascular Twins, AI Agents, and Sensor Data: A Narrative Review from System Architecture to Proactive Heart Health.Sensors (Basel, Switzerland) · 2025Review
- Use of Continuous Positive Airway Pressure Ventilation as a Support During Coronary Angioplasty in Patients with Acute Myocardial Infarction: Safety and Feasibility.Journal of clinical medicine · 2025Article
- Artificial intelligence-powered advancements in atrial fibrillation diagnostics: a systematic review.The Egyptian heart journal : (EHJ) : official bulletin of the Egyptian Society of Cardiology · 2025Review
- Bridging the Gap Between Artificial Intelligence Understanding and Clinical Implementation in Cardiovascular Medicine: A Commentary on Heinrich and Voigt's Review.Clinical cardiology · 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
Artificial intelligence (AI) is being intensively applied to cardiology, particularly in diagnostics, risk prediction, treatment planning, and invasive procedures. While AI-driven advancements have demonstrated promise, their real-world implementation remains constrained by critical challenges. Current AI applications, such as electrocardiogram interpretation and automated imaging analysis, have improved diagnostic accuracy and workflow efficiency, yet generalizability, regulatory hurdles, and integration into existing clinical workflows remain major obstacles. Algorithmic bias and the lack of explainable AI further complicate widespread adoption, potentially leading to disparities in healthcare outcomes. In interventional cardiology, robotic-assisted percutaneous coronary intervention has emerged as a technological innovation, but comparative clinical evidence supporting its superiority (or even non-inferiority) over conventional approaches is still limited. Additionally, AI-based decision support systems in high-risk cardiovascular procedures require rigorous validation to ensure safety and reliability. Ethical considerations, including patient data security and region-specific regulatory frameworks, also pose significant barriers. Addressing these challenges requires interdisciplinary collaboration, robust external validation, and the development of transparent, interpretable AI models. This review provides a critical appraisal of the current role of AI in cardiology, emphasizing both its potential and its limitations, and outlines future directions to facilitate its responsible integration into clinical practice.
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.