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Management and outcomes of patients with left atrial appendage thrombus prior to percutaneous closure Alcohol consumption, cardiac biomarkers, and risk of atrial fibrillation and adverse outcomes Evolving insights into the role of local shear stress in late stent failure from neoatherosclerosis formation and plaque destabilization Single direct oral anticoagulant therapy in stable patients with atrial fibrillation beyond 1 year after coronary stent implantation Hemodynamic, Functional, and Clinical Responses to Pulmonary Artery Denervation in Patients With Pulmonary Arterial Hypertension of Different Causes Functional Mitral Regurgitation Outcome and Grading in Heart Failure With Reduced Ejection Fraction Strain-Guided Management of Potentially Cardiotoxic Cancer Therapy Rivaroxaban for Thromboprophylaxis in High-Risk Ambulatory Patients With Cancer Long-Term Outcomes of Patients With Mediastinal Radiation–Associated Coronary Artery Disease Undergoing Coronary Revascularization With Percutaneous Coronary Intervention and Coronary Artery Bypass Grafting Left Atrial Appendage Closure versus Non-Warfarin Oral Anticoagulation in Atrial Fibrillation: 4-Year Outcomes of PRAGUE-17

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.