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Antithrombotic Therapy in Patients with Atrial Fibrillation and Acute Coronary Syndrome Treated Medically or with Percutaneous Coronary Intervention or Undergoing Elective Percutaneous Coronary Intervention: Insights from the AUGUSTUS Trial Contemporary Management of Cardiogenic Shock: A Scientific Statement From the American Heart Association Fourth Universal Definition of Myocardial Infarction (2018) Transcatheter Aortic-Valve Replacement with a Self-Expanding Valve in Low-Risk Patients A Randomized Trial of a 1-Hour Troponin T Protocol in Suspected Acute Coronary Syndromes: The Rapid Assessment of Possible ACS In the Emergency Department with High Sensitivity Troponin T (RAPID-TnT) Study Current Interventions for the Left Main Bifurcation Investigating methotrexate toxicity within a randomized double-blinded, placebo-controlled trial: Rationale and design of the Cardiovascular Inflammation Reduction Trial-Adverse Events (CIRT-AE) Study One or two stents for the distal Left Main bifurcation The DK crush V study - The DK crush V study 2017 ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation: The Task Force for the management of acute myocardial infarction in patients presenting with ST-segment elevation of the European Society of Cardiology (ESC) Astro-CHARM, the First 10-year ASCVD Risk Estimator Incorporating Coronary Calcium
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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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