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Coronary artery bypass graft surgery versus percutaneous coronary intervention in patients with three-vessel disease and left main coronary disease: 5-year follow-up of the randomised, clinical SYNTAX trial Qualitative and Mixed Methods Provide Unique Contributions to Outcomes Research Intravascular Ultrasound Guidance Reduces Cardiac Death and Coronary Revascularization in Patients Undergoing Drug-Eluting Stent Implantation: Results From a Meta-Analysis of 9 Randomized Trials and 4724 Patients Mitral Valve Remodeling and Strain in Secondary Mitral Regurgitation: Comparison With Primary Regurgitation and Normal Valves Association of loop diuretics use and dose with outcomes in outpatients with heart failure: a systematic review and meta-analysis of observational studies involving 96,959 patients Antithrombotics From Aspirin to DOACs in Coronary Artery Disease and Atrial Fibrillation (Part 3/5) 2-year outcomes with the Absorb bioresorbable scaffold for treatment of coronary artery disease: a systematic review and meta-analysis of seven randomised trials with an individual patient data substudy IVUS Guidance for Coronary Revascularization: When to Start, When to Stop? Is Acute heart failure a distinctive disorder? An analysis from BIOSTAT-CHF Impact of different final optimization techniques on long-term clinical outcomes of left main cross-over stenting

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.