Author + information
- Received August 8, 2018
- Revision received February 26, 2019
- Accepted April 2, 2019
- Published online July 15, 2019.
- Partha Sardar, MDa,
- J. Dawn Abbott, MDa,
- Amartya Kundu, MDb,
- Herbert D. Aronow, MDa,
- Juan F. Granada, MDc and
- Jay Giri, MD, MPHd,e,∗ (, )@parthasardarmd@jaygirimd
- aCardiovascular Institute, Warren Alpert Medical School at Brown University, Providence, Rhode Island
- bDivision of Cardiovascular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts
- cCardiovascular Research Foundation, Columbia University Medical Center, New York, New York
- dPenn Cardiovascular Outcomes, Quality and Evaluative Research Center, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania
- eCardiovascular Medicine Division, University of Pennsylvania, Philadelphia, Pennsylvania
- ↵∗Address for correspondence:
Dr. Jay Giri, Hospital of the University of Pennsylvania, Cardiovascular Medicine Division, Gates Pavilion, 9th Floor, 3400 Spruce Street, Philadelphia, Pennsylvania 19104.
• The field of AI has initiated a paradigm shift in health care with advanced analytical techniques.
• Potential applications of AI in IC are image and video analysis, clinical decision support, robotic assistance with procedure, and novel approaches to clinical database analysis.
• The current development of AI in IC is in its early stage, but it has the potential to transform IC practice.
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.
Dr. Granada has received institutional grant/research support (to Skirball Center for Innovation) from Abbott Vascular, Amaranth Medical, Amber Medical, Amgen, Baylis, BIO2 Medical, Bristol-Myers Squibb, Boston Scientific, Cagent Vascular, Caliber Therapeutics, Cephea, Columbia Medical, Corindus Vascular, Celyad, Freudenberg Medical, Intact Vascular, JenaValve, Keystone Heart, LimFlow Medical, LoneStar Heart, Marvel Medical, Medtronic, Meril Life Sciences, MicroVention, Motus GI, Navigate Cardiac Structures, New York University, OrbusNeich Medical, SoundBite Medical, Spectranetics, Toray Industries, Vetex Medical, Volcano (Philips), and Zimmer Biomet. Dr. Giri has served on an advisory board for AstraZeneca; and has received research support to the institution from Recor Medical and Abbott Vascular. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
- Received August 8, 2018.
- Revision received February 26, 2019.
- Accepted April 2, 2019.
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