Current and Future Applications of Artificial Intelligence in Coronary Artery Disease

Nitesh Gautam, Prachi Saluja, Abdallah Malkawi, Mark G. Rabbat, Mouaz H. Al-Mallah, Gianluca Pontone, Yiye Zhang, Benjamin C. Lee, Subhi J. Al’Aref

Research output: Contribution to journalReview articlepeer-review

Abstract

Cardiovascular diseases (CVDs) carry significant morbidity and mortality and are associated with substantial economic burden on healthcare systems around the world. Coronary artery disease, as one disease entity under the CVDs umbrella, had a prevalence of 7.2% among adults in the United States and incurred a financial burden of 360 billion US dollars in the years 2016–2017. The introduction of artificial intelligence (AI) and machine learning over the last two decades has unlocked new dimensions in the field of cardiovascular medicine. From automatic interpretations of heart rhythm disorders via smartwatches, to assisting in complex decision-making, AI has quickly expanded its realms in medicine and has demonstrated itself as a promising tool in helping clinicians guide treatment decisions. Understanding complex genetic interactions and developing clinical risk prediction models, advanced cardiac imaging, and improving mortality outcomes are just a few areas where AI has been applied in the domain of coronary artery disease. Through this review, we sought to summarize the advances in AI relating to coronary artery disease, current limitations, and future perspectives.

Original languageEnglish (US)
Article number232
JournalHealthcare (Switzerland)
Volume10
Issue number2
DOIs
StatePublished - Feb 2022

Keywords

  • Artificial intelligence
  • Cardiac computed tomography
  • Coronary artery disease
  • Fractional flow reserve
  • Major adverse cardiovascular events

ASJC Scopus subject areas

  • Health Informatics
  • Health Policy
  • Health Information Management
  • Leadership and Management

Fingerprint

Dive into the research topics of 'Current and Future Applications of Artificial Intelligence in Coronary Artery Disease'. Together they form a unique fingerprint.

Cite this