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A Combined Optical Coherence Tomography and Intravascular Ultrasound Study on Plaque Rupture, Plaque Erosion, and Calcified Nodule in Patients With ST-Segment Elevation Myocardial Infarction: Incidence, Morphologic Characteristics, and Outcomes After Percutaneous Coronary Intervention Comparison of safety and periprocedural complications of transfemoral aortic valve replacement under local anaesthesia: minimalist versus complete Heart Team Longitudinal Change in Galectin-3 and Incident Cardiovascular Outcomes Heart Failure With Recovered Left Ventricular Ejection Fraction: JACC Scientific Expert Panel Prognostic implications of baseline 6‐min walk test performance in intermediate risk patients undergoing transcatheter aortic valve replacement Colchicine Reduces Cardiovascular Events in Chronic Coronary Disease The Evolution of β-Blockers in Coronary Artery Disease and Heart Failure (Part 1/5) Incidence and Outcomes of Surgical Bailout During TAVR : Insights From the STS/ACC TVT Registry Impact of Positive and Negative Lesion Site Remodeling on Clinical Outcomes : Insights From PROSPECT From organic and inorganic phosphates to valvular and vascular calcifications
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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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