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P2Y12 Inhibitor Monotherapy with Clopidogrel Versus Ticagrelor in Patients with Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention Positive remodeling at 3 year follow up is associated with plaque-free coronary wall segment at baseline: a serial IVUS study The role of integrated backscatter intravascular ultrasound in characterizing bare metal and drug-eluting stent restenotic neointima as compared to optical coherence tomography Valve‐in‐Valve for Degenerated Transcatheter Aortic Valve Replacement Versus Valve‐in‐Valve for Degenerated Surgical Aortic Bioprostheses: A 3‐Center Comparison of Hemodynamic and 1‐Year Outcome A Prospective, Multicenter, Randomized, Open-label Trial to Compare Efficacy and Safety of Clopidogrel vs. Ticagrelor in Stabilized Patients with Acute Myocardial Infarction after Percutan eous Coronary Intervention: rationale and design of the TALOS-AMI trial Comparison of newer generation self-expandable vs. balloon-expandable valves in transcatheter aortic valve implantation: the randomized SOLVE-TAVI trial Association of White Matter Hyperintensities and Cardiovascular Disease: The Importance of Microcirculatory Disease Edoxaban versus Vitamin K Antagonist for Atrial Fibrillation after TAVR Impact of Staging Percutaneous Coronary Intervention in Left Main Artery Disease: Insights From the EXCEL Trial Right ventricular function and outcome in patients undergoing transcatheter aortic valve replacement
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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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