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Clinical Impact of Suboptimal Stenting and Residual Intrastent Plaque/Thrombus Protrusion in Patients With Acute Coronary Syndrome: The CLI-OPCI ACS Substudy (Centro per la Lotta Contro L'Infarto-Optimization of Percutaneous Coronary Intervention in Acute Coronary Syndrome) Coronary Physiology in the Cardiac Catheterization Laboratory Effect of low-density lipoprotein cholesterol on the geometry of coronary bifurcation lesions and clinical outcomes of coronary interventions in the J-REVERSE registry Characteristics of abnormal post-stent optical coherence tomography findings in hemodialysis patients Coronary Microcirculation Downstream Non-Infarct-Related Arteries in the Subacute Phase of Myocardial Infarction: Implications for Physiology-Guided Revascularization Cardiotoxicity and Cardiac Monitoring Among Chemotherapy-Treated Breast Cancer Patients Japan-United States of America Harmonized Assessment by Randomized Multicentre Study of OrbusNEich's Combo StEnt (Japan-USA HARMONEE) study: primary results of the pivotal registration study of combined endothelial progenitor cell capture and drug-eluting stent in patients with ischaemic coronary disease and non-ST-elevation acute coronary syndrome Update on chronic thromboembolic pulmonary hypertension Genetic analyses in a cohort of 191 pulmonary arterial hypertension patients Immunotherapy of Endothelin-1 Receptor Type A for Pulmonary Arterial Hypertension
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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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