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Three vs twelve months of dual antiplatelet therapy after zotarolimus-eluting stents: the OPTIMIZE randomized trial 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure ACC/AHA Versus ESC Guidelines on Dual Antiplatelet Therapy JACC Guideline Comparison: JACC State-of-the-Art Review Clinical Phenogroups in Heart Failure With Preserved Ejection Fraction: Detailed Phenotypes, Prognosis, and Response to Spironolactone Transcatheter Aortic Valve Implantation Represents an Anti-Inflammatory Therapy Via Reduction of Shear Stress-Induced, Piezo-1-Mediated Monocyte Activation Haptoglobin genotype: a determinant of cardiovascular complication risk in type 1 diabetes Noninvasive Imaging for the Evaluation of Diastolic Function: Promises Fulfilled Proteomics to Improve Phenotyping in Obese Patients with Heart Failure with Preserved Ejection Fraction Effects of Icosapent Ethyl on Total Ischemic Events: From REDUCE-IT Baseline Characteristics and Risk Profiles of Participants in the ISCHEMIA Randomized Clinical Trial

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.