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Mechanical complications of everolimus-eluting stents associated with adverse events: an intravascular ultrasound study Association of Prior Left Ventricular Ejection Fraction With Clinical Outcomes in Patients With Heart Failure With Midrange Ejection Fraction Plaque composition by intravascular ultrasound and distal embolization after percutaneous coronary intervention Circulating sST2 and catestatin levels in patients with acute worsening of heart failure: a report from the CATSTAT-HF study Clinical impact of intravascular ultrasound-guided chronic total occlusion intervention with zotarolimus-eluting versus biolimus-eluting stent implantation: randomized study Association of Smoking Status With Long‐Term Mortality and Health Status After Transcatheter Aortic Valve Replacement: Insights From the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry Cardiac Resynchronization Therapy and Ventricular Tachyarrhythmia Burden Cardiac Resynchronization Therapy in Inotrope-Dependent Heart Failure Patients - A Systematic Review and Meta-Analysis Meta-analysis of outcomes after intravascular ultrasound-guided versus angiography-guided drug-eluting stent implantation in 26,503 patients enrolled in three randomized trials and 14 observational studies Canagliflozin and Cardiovascular and Renal Events in Type 2 Diabetes
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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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