Artificial Intelligence for Cardiovascular Care—Part 1: Advances: JACC Review Topic of the Week

Pierre Elias, Sneha S. Jain, Timothy Poterucha, Michael Randazzo, Francisco Lopez Jimenez, Rohan Khera, Marco Perez, David Ouyang, James Pirruccello, Michael Salerno, Andrew J. Einstein, Robert Avram, Geoffrey H. Tison, Girish Nadkarni, Vivek Natarajan, Emma Pierson, Ashley Beecy, Deepa Kumaraiah, Chris Haggerty, Jennifer N. Avari SilvaThomas M. Maddox

Research output: Contribution to journalReview articlepeer-review

12 Scopus citations

Abstract

Recent artificial intelligence (AI) advancements in cardiovascular care offer potential enhancements in diagnosis, treatment, and outcomes. Innovations to date focus on automating measurements, enhancing image quality, and detecting diseases using novel methods. Applications span wearables, electrocardiograms, echocardiography, angiography, genetics, and more. AI models detect diseases from electrocardiograms at accuracy not previously achieved by technology or human experts, including reduced ejection fraction, valvular heart disease, and other cardiomyopathies. However, AI's unique characteristics necessitate rigorous validation by addressing training methods, real-world efficacy, equity concerns, and long-term reliability. Despite an exponentially growing number of studies in cardiovascular AI, trials showing improvement in outcomes remain lacking. A number are currently underway. Embracing this rapidly evolving technology while setting a high evaluation benchmark will be crucial for cardiology to leverage AI to enhance patient care and the provider experience.

Original languageEnglish
Pages (from-to)2472-2486
Number of pages15
JournalJournal of the American College of Cardiology
Volume83
Issue number24
DOIs
StatePublished - Jun 18 2024

Keywords

  • artificial intelligence
  • cardiac imaging
  • deep learning
  • digital health
  • innovation
  • large language models
  • machine learning

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