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Cardiovascular Mortality After Type 1 and Type 2 Myocardial Infarction in Young Adults Stent fracture is associated with a higher mortality in patients with type-2 diabetes treated by implantation of a second-generation drug-eluting stent Comparison of Stent Expansion Guided by Optical Coherence Tomography Versus Intravascular Ultrasound: The ILUMIEN II Study (Observational Study of Optical Coherence Tomography [OCT] in Patients Undergoing Fractional Flow Reserve [FFR] and Percutaneous Coronary Intervention) Left Ventricular Assist Device as a Bridge to Recovery for Patients With Advanced Heart Failure Association of Parenteral Anticoagulation Therapy With Outcomes in Chinese Patients Undergoing Percutaneous Coronary Intervention for Non-ST-Segment Elevation Acute Coronary Syndrome LOX-1 in Atherosclerosis and Myocardial Ischemia: Biology, Genetics, and Modulation Randomized trial of complete versus lesion-only revascularization in patients undergoing primary percutaneous coronary intervention for STEMI and multivessel disease: the CvLPRIT trial Defining Staged Procedures for Percutaneous Coronary Intervention Trials A Guidance Document Interval From Initiation of Prasugrel to Coronary Angiography in Patients With Non–ST-Segment Elevation Myocardial Infarction Impact of Off-Hours Versus On-Hours Primary Percutaneous Coronary Intervention on Myocardial Damage and Clinical Outcomes in ST-Segment Elevation Myocardial Infarction
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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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