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Heart Failure With Improved Ejection Fraction-Is it Possible to Escape One’s Past? Is Cardiac Diastolic Dysfunction a Part of Post-Menopausal Syndrome? Rationale and design of the GUIDE-IT study: Guiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart Failure Aliskiren, Enalapril, or Aliskiren and Enalapril in Heart Failure Nocturnal thoracic volume overload and post-discharge outcomes in patients hospitalized for acute heart failure Identifying coronary artery disease patients at risk for sudden and/or arrhythmic death: remaining limitations of the electrocardiogram The Prevalence of Myocardial Bridging Associated with Coronary Endothelial Dysfunction in Patients with Chest Pain and Non-Obstructive Coronary Artery Disease Association of Cardiovascular Disease With Respiratory Disease Meta-analysis of outcomes after intravascular ultrasound-guided versus angiography-guided drug-eluting stent implantation in 26,503 patients enrolled in three randomized trials and 14 observational studies Increased glycated albumin and decreased esRAGE levels in serum are related to negative coronary artery remodeling in patients with type 2 diabetes: an Intravascular ultrasound 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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