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Impact of lesion complexity on peri-procedural adverse events and the benefit of potent intravenous platelet adenosine diphosphate receptor inhibition after percutaneous coronary intervention: core laboratory analysis from 10 854 patients from the CHAMPION PHOENIX trial Cardiovascular Biomarkers and Imaging in Older Adults: JACC Council Perspectives Individualizing Revascularization Strategy for Diabetic Patients With Multivessel Coronary Disease Transcatheter Mitral-Valve Repair in Patients with Heart Failure Long-term Survival following Multivessel Revascularization in Patients with Diabetes (FREEDOM Follow-On Study) Advances in Coronary No-Reflow Phenomenon-a Contemporary Review Radial Versus Femoral Access for Coronary Interventions Across the Entire Spectrum of Patients With Coronary Artery Disease: A Meta-Analysis of Randomized Trials Optimal Stenting Technique for Complex Coronary Lesions Intracoronary Imaging-Guided Pre-Dilation, Stent Sizing, and Post-Dilation 2015 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: Task Force for the Management of Acute Coronary Syndromes in Patients Presenting without Persistent ST-Segment Elevation of the European Society of Cardiology (ESC) The Prognostic Value of Exercise Echocardiography After Percutaneous Coronary Intervention

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.