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Frequency of nonsystem delays in ST-elevation myocardial infarction patients undergoing primary percutaneous coronary intervention and implications for door-to-balloon time reporting (from the American Heart Association Mission: Lifeline program) Surgical or Transcatheter Aortic-Valve Replacement in Intermediate-Risk Patients Prognostic Implication of Thermodilution Coronary Flow Reserve in Patients Undergoing Fractional Flow Reserve Measurement Association of Acute Procedural Results with Long-term Outcomes After CTO-PCI Spontaneous Coronary Artery Dissection: JACC State-of-the-Art Review How Low to Go With Glucose, Cholesterol, and Blood Pressure in Primary Prevention of CVD The Future of Cardiovascular Computed Tomography Advanced Analytics and Clinical Insights 2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes: The Task Force for the diagnosis and management of chronic coronary syndromes of the European Society of Cardiology (ESC) De-escalation of antianginal medications after successful chronic total occlusion percutaneous coronary intervention: Frequency and relationship with health status

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.