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Comparison in prevalence, predictors, and clinical outcome of VSR versus FWR after acute myocardial infarction: The prospective, multicenter registry MOODY trial-heart rupture analysis Cardiac Troponin Composition Characterization after Non ST-Elevation Myocardial Infarction: Relation with Culprit Artery, Ischemic Time Window, and Severity of Injury Uptake of Drug-Eluting Bioresorbable Vascular Scaffolds in Clinical Practice : An NCDR Registry to Practice Project Natural History of Spontaneous Coronary Artery Dissection With Spontaneous Angiographic Healing Myocardial Inflammation Predicts Remodeling and Neuroinflammation After Myocardial Infarction Contemporary Diagnosis and Management of Patients With Myocardial Infarction in the Absence of Obstructive Coronary Artery Disease: A Scientific Statement From the American Heart Association Patient Characteristics Associated With Antianginal Medication Escalation and De-Escalation Following Chronic Total Occlusion Percutaneous Coronary Intervention: Insights From the OPEN CTO Registry High-sensitivity troponin in the evaluation of patients with suspected acute coronary syndrome: a stepped-wedge, cluster-randomised controlled trial Impact of Oxidative Stress on the Heart and Vasculature: Part 2 of a 3-Part Series 2014 AHA/ACC Guideline for the Management of Patients with Non-ST-Elevation Acute Coronary Syndromes: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines
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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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