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Association of Circulating Monocyte Chemoattractant Protein-1 Levels With Cardiovascular Mortality: A Meta-analysis of Population-Based Studies Switching of Oral Anticoagulation Therapy After PCI in Patients With Atrial Fibrillation: The RE-DUAL PCI Trial Subanalysis Empagliflozin and Progression of Kidney Disease in Type 2 Diabetes Relation between baseline plaque features and subsequent coronary artery remodeling determined by optical coherence tomography and intravascular ultrasound Five-Year Outcomes of Transcatheter or Surgical Aortic-Valve Replacement Cardiac Structural Changes After Transcatheter Aortic Valve Replacement: Systematic Review and Meta-Analysis of Cardiovascular Magnetic Resonance Studies Association of Reduced Apical Untwisting With Incident HF in Asymptomatic Patients With HF Risk Factors INTERMACS Profiles and Outcomes Among Non–Inotrope-Dependent Outpatients With Heart Failure and Reduced Ejection Fraction Utility of intravascular ultrasound guidance in patients undergoing percutaneous coronary intervention for type C lesions The effect of complete percutaneous revascularisation with and without intravascular ultrasound guidance in the drugeluting stent era
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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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