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Coronary calcium as a predictor of coronary events in four racial or ethnic groups Second vs. First generation drug eluting stents in multiple vessel disease and left main stenosis: Two-year follow-up of the observational, prospective, controlled, and multicenter ERACI IV registry Contemporary Presentation and Management of Valvular Heart Disease: The EURObservational Research Programme Valvular Heart Disease II Survey Diagnostic accuracy of cardiac positron emission tomography versus single photon emission computed tomography for coronary artery disease: a bivariate meta-analysis Transcatheter Aortic Valve Replacement in Patients With Multivalvular Heart Disease 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk: The Task Force for the management of dyslipidaemias of the European Society of Cardiology (ESC) and European Atherosclerosis Society (EAS) Long-term results after PCI of unprotected distal left main coronary artery stenosis: the Bifurcations Bad Krozingen (BBK)-Left Main Registry Long-Term All-Cause and Cause-Specific Mortality in Asymptomatic Patients With CAC ≥1,000: Results From the CAC Consortium Myocardial bridging of the left anterior descending coronary artery is associated with reduced myocardial perfusion reserve: a 13N-ammonia PET study Complex PCI procedures: challenges for the interventional cardiologist
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Review ArticleVolume 12, Issue 14, July 2019

JOURNAL：JACC Cardiovasc Interv. Article Link

Impact of Artificial Intelligence on Interventional Cardiology: From Decision-Making Aid to Advanced Interventional Procedure Assistance

P Sardar, JD Abbott, A Kundu et al. Keywords: artificial intelligence; interventional cardiology

ABSTRACT

Access to big data analyzed by supercomputers using advanced mathematical algorithms (i.e., deep machine learning) has allowed for enhancement of cognitive output (i.e., visual imaging interpretation) to previously unseen levels and promises to fundamentally change the practice of medicine. This field, known as “artificial intelligence” (AI), is making significant progress in areas such as automated clinical decision making, medical imaging analysis, and interventional procedures, and has the potential to dramatically influence the practice of interventional cardiology. The unique nature of interventional cardiology makes it an ideal target for the development of AI-based technologies designed to improve real-time clinical decision making, streamline workflow in the catheterization laboratory, and standardize catheter-based procedures through advanced robotics. This review provides an introduction to AI by highlighting its scope, potential applications, and limitations in interventional cardiology.

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