Electrocardiographic biosignals to predict atrial fibrillation: Are we there yet?

Anthony H. Kashou, Peter A. Noseworthy

Research output: Contribution to journalArticlepeer-review

Abstract

The prevalence of atrial fibrillation (AF) continues to grow in an aging population, and its impact on both patients and the health care system has has made it a global burden. There are limited available options to detect individuals at risk of AF that may benefit from prevention and treatment strategies. The ECG may be an effective tool do so. In this work, we discuss the latest work by Hayiroğlu and colleagues related to this work and the use of novel ECG prediction tools to identify individuals individuals that could benefit from early and proactive screening, surveillance, and management strategies.

Original languageEnglish (US)
Pages (from-to)37-38
Number of pages2
JournalJournal of Electrocardiology
Volume70
DOIs
StatePublished - Jan 1 2022

Keywords

  • Artificial intelligence
  • Atrial cardiopathy
  • Atrial fibrillation
  • ECG
  • Electrocardiogram
  • Interatrial block
  • Ischemic stroke
  • Machine learning

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

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