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Impact of percutaneous coronary intervention extent, complexity and platelet reactivity on outcomes after drug-eluting stent implantation Individualizing Revascularization Strategy for Diabetic Patients With Multivessel Coronary Disease Incidence, predictors, and outcomes of DAPT disruption due to non-compliance vs. bleeding after PCI: insights from the PARIS Registry Comparison of Accuracy of One-Use Methods for Calculating Fractional Flow Reserve by Intravascular Optical Coherence Tomography to That Determined by the Pressure-Wire Method SCAI clinical expert consensus statement on the classification of cardiogenic shock: This document was endorsed by the American College of Cardiology (ACC), the American Heart Association (AHA), the Society of Critical Care Medicine (SCCM), and the Society of Thoracic Surgeons (STS) in April 2019 Association of Coronary Anatomical Complexity With Clinical Outcomes After Percutaneous or Surgical Revascularization in the Veterans Affairs Clinical Assessment Reporting and Tracking Program Randomized Comparison Between Radial and Femoral Large-Bore Access for Complex Percutaneous Coronary Intervention The Prognostic Value of Exercise Echocardiography After Percutaneous Coronary Intervention Switching P2Y12-receptor inhibitors in patients with coronary artery disease Predicting Major Adverse Events in Patients With Acute Myocardial Infarction
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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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