The role of automated 12-lead ECG interpretation in the diagnosis and risk stratification of cardiovascular disease

Salah Al-Zaiti, Ziad Faramand, Khaled Rjoob, D Finlay, RR Bond

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The electrocardiogram (ECG) is the most widely used diagnostic test in clinical settings. The ECG signal is well-understood and its use in clinical applications is regulated by widely adopted clinical practice guidelines. Computer-aided automated ECG interpretations, hence, play an important role in cardiovascular disease diagnostics and risk stratification. This chapter will provide a comprehensive overview of the cellular and electrical basis of cardiac electrophysiology, technical specifications that govern electrocardiography, the current standards of automated ECG interpretation algorithms, machine learning applications in ECG interpretation, and the role of interpretation automation in diagnostic and risk stratification. Challenges, limitations, and future opportunities of computer-aided ECG diagnostics are also summarized.
Original languageEnglish
Title of host publicationCardiovascular and Coronary Artery Imaging
EditorsAyman S. El-Baz, Jasjit Suri
PublisherElsevier
Chapter3
Pages45-87
Volume1
ISBN (Electronic)9780128227077
ISBN (Print)9780128227060
DOIs
Publication statusPublished (in print/issue) - 26 Nov 2021

Keywords

  • automated interpretation
  • 12-lead ECG
  • AI
  • machine learning
  • cardiovascular disease

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