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Frequency, Regional Variation, and Predictors of Undetermined Cause of Death in Cardiometabolic Clinical Trials: A Pooled Analysis of 9259 Deaths in 9 Trials Management of No-Reflow Phenomenon in the Catheterization Laboratory Considerations for Single-Measurement Risk-Stratification Strategies for Myocardial Infarction Using Cardiac Troponin Assays Percutaneous Repair or Medical Treatment for Secondary Mitral Regurgitation Outcomes after drug-coated balloon treatment for patients with calcified coronary lesions A Novel Familial Cardiac Arrhythmia Syndrome with Widespread ST-Segment Depression Screening for Cardiovascular Disease Risk With Electrocardiography: US Preventive Services Task Force Recommendation Statement ACC/AATS/AHA/ASE/ASNC/HRS/SCAI/SCCT/SCMR/STS 2019 Appropriate Use Criteria for Multimodality Imaging in the Assessment of Cardiac Structure and Function in Nonvalvular Heart Disease: A Report of the American College of Cardiology Appropriate Use Criteria Task Force, American Association for Thoracic Surgery, American Heart Association, American Society of Echocardiography, American Society of Nuclear Cardiology, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Cardiovascular Computed Tomography, Society for Cardiovascular Magnetic Resonance, and the Society of Thoracic Surgeons Current Perspectives on Coronavirus Disease 2019 and Cardiovascular Disease: A White Paper by the JAHA Editors Percutaneous coronary intervention using a combination of robotics and telecommunications by an operator in a separate physical location from the patient: an early exploration into the feasibility of telestenting (the REMOTE-PCI study)
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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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