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Radial Versus Femoral Access for Coronary Interventions Across the Entire Spectrum of Patients With Coronary Artery Disease: A Meta-Analysis of Randomized Trials Combining IVUS and Optical Coherence Tomography for More Accurate Coronary Cap Thickness Quantification and Stress/Strain Calculations: A Patient-Specific Three-Dimensional Fluid-Structure Interaction Modeling Approach Changes in One-Year Mortality in Elderly Patients Admitted with Acute Myocardial Infarction in Relation with Early Management The HACD4 haplotype as a risk factor for atherosclerosis in males Prospective Elimination of Distal Coronary Sinus to Left Atrial Connection for Atrial Fibrillation Ablation (PRECAF) Randomized Controlled Trial Association of the PHACTR1/EDN1 Genetic Locus With Spontaneous Coronary Artery Dissection The Impact of Proximal Vessel Tortuosity on the Outcomes of Chronic Total Occlusion Percutaneous Coronary Intervention: Insights From a Contemporary Multicenter Registry Eruptive Calcified Nodules as a Potential Mechanism of Acute Coronary Thrombosis and Sudden Death Long-term Survival following Multivessel Revascularization in Patients with Diabetes (FREEDOM Follow-On Study) Acute Noncardiac Organ Failure in Acute Myocardial Infarction With Cardiogenic Shock
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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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