CBS 2019
CBSMD教育中心
中 文

Other Relevant Articles

Abstract

Recommended Article

Burden of 30-Day Readmissions After Percutaneous Coronary Intervention in 833,344 Patients in the United States: Predictors, Causes, and Cost Quantitative angiography methods for bifurcation lesions: a consensus statement update from the European Bifurcation Club Association Between Living in Food Deserts and Cardiovascular Risk 2017 ESC Guidelines on the Diagnosis and Treatment of Peripheral Arterial Diseases, in collaboration with the European Society for Vascular Surgery (ESVS): Document covering atherosclerotic disease of extracranial carotid and vertebral, mesenteric, renal, upper and lower extremity arteries Endorsed Effects of Aspirin for Primary Prevention in Persons with Diabetes Mellitus Antithrombotic Therapy after Acute Coronary Syndrome or PCI in Atrial Fibrillation Temporal trends in percutaneous coronary interventions thru the drug eluting stent era: Insights from 18,641 procedures performed over 12-year period Blood CSF1 and CXCL12 as Causal Mediators of Coronary Artery Disease

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.