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IVUS-Guided vs Angiography-Guided PCI in Patients With Diabetes With Acute Coronary Syndromes: The IVUS-ACS Trial Rationale and design of the Women's Ischemia Trial to Reduce Events in Nonobstructive CAD (WARRIOR) trial Intravascular ultrasound-guided versus angiography-guided percutaneous coronary intervention in acute coronary syndromes (IVUS-ACS): a two-stage, multicentre, randomised trial m6A Modification of Profilin-1 in Vascular Smooth Muscle Cells Drives Phenotype Switching and Neointimal Hyperplasia via Activation of the p-ANXA2/STAT3 Pathway Lowering systolic blood pressure to less than 120 mm Hg versus less than 140 mm Hg in patients with high cardiovascular risk with and without diabetes or previous stroke: an open-label,blinded-outcome,randomised trial Establishment of a canine model of pulmonary arterial hypertension induced by dehydromonocrotaline and ultrasonographic study of right ventricular remodeling GRK2–YAP signaling is implicated in pulmonary arterial hypertension development High-Risk Plaques on Coronary Computed Tomography Angiography: Correlation With Optical Coherence Tomography Intravascular Ultrasound vs Angiography-Guided Drug-Coated Balloon Angioplasty: The ULTIMATE Ⅲ Trial Drug-Coated Balloon Angioplasty of the Side Branch During Provisional Stenting: The Multicenter Randomized DCB-BIF Trial

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.