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16-05-2024 | Electrocardiography | Invasive Electrophysiology and Pacing (EK Heist, Section Editor)

Artificial Intelligence Interpretation of the Electrocardiogram: A State-of-the-Art Review

Authors: Benjamin Ose, Zeeshan Sattar, Amulya Gupta, Christian Toquica, Chris Harvey, Amit Noheria

Published in: Current Cardiology Reports | Issue 6/2024

Abstract

Purpose of Review

Artificial intelligence (AI) is transforming electrocardiography (ECG) interpretation. AI diagnostics can reach beyond human capabilities, facilitate automated access to nuanced ECG interpretation, and expand the scope of cardiovascular screening in the population. AI can be applied to the standard 12-lead resting ECG and single-lead ECGs in external monitors, implantable devices, and direct-to-consumer smart devices. We summarize the current state of the literature on AI-ECG.

Recent Findings

Rhythm classification was the first application of AI-ECG. Subsequently, AI-ECG models have been developed for screening structural heart disease including hypertrophic cardiomyopathy, cardiac amyloidosis, aortic stenosis, pulmonary hypertension, and left ventricular systolic dysfunction. Further, AI models can predict future events like development of systolic heart failure and atrial fibrillation. AI-ECG exhibits potential in acute cardiac events and non-cardiac applications, including acute pulmonary embolism, electrolyte abnormalities, monitoring drugs therapy, sleep apnea, and predicting all-cause mortality.

Summary

Many AI models in the domain of cardiac monitors and smart watches have received Food and Drug Administration (FDA) clearance for rhythm classification, while others for identification of cardiac amyloidosis, pulmonary hypertension and left ventricular dysfunction have received breakthrough device designation. As AI-ECG models continue to be developed, in addition to regulatory oversight and monetization challenges, thoughtful clinical implementation to streamline workflows, avoiding information overload and overwhelming of healthcare systems with false positive results is necessary. Research to demonstrate and validate improvement in healthcare efficiency and improved patient outcomes would be required before widespread adoption of any AI-ECG model.

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Title: Artificial Intelligence Interpretation of the Electrocardiogram: A State-of-the-Art Review
Authors: Benjamin Ose
Zeeshan Sattar
Amulya Gupta
Christian Toquica
Chris Harvey
Amit Noheria
Publication date: 16-05-2024
Publisher: Springer US
Keywords: Electrocardiography
Artificial Intelligence
Artificial Intelligence in Healthcare
Electrocardiography
Atrial Fibrillation
Cardiomyopathy
Aortic Valve Stenosis
Pulmonary Hypertension
Published in: Current Cardiology Reports / Issue 6/2024
Print ISSN: 1523-3782
Electronic ISSN: 1534-3170
DOI: https://doi.org/10.1007/s11886-024-02062-1

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Keynote webinar | Spotlight on medication adherence

Webinar | 27-06-2024 | 18:00 (CEST)

Medication non-adherence is a major barrier to effective healthcare delivery; half of all patients do not follow their doctor’s recommendations or treatment plan.

Our experts explain the fundamentals with a practical discussion of how to manage non-adherence in two common scenarios: hypertension and asthma control.

Prof. Kevin Dolgin

Prof. Florian Limbourg

Prof. Anoop Chauhan

Developed by: Springer Medicine

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EASD 2024

Springer Medicine

Artificial Intelligence Interpretation of the Electrocardiogram: A State-of-the-Art Review

Abstract

Purpose of Review

Recent Findings

Summary

2024 ESC Congress

Noise pollution dangerous for heart health

Post-TAVI follow up: deploying virtual assistants

Antihypertensives: more effective at morning or night?

Low Lp(a) levels unlikely to increase the risk of diabetes

» View more highlights on the 2024 ESC Congress hub page

A quick guide to ECGs

Keynote webinar | Spotlight on medication adherence

EASD 2024

Springer Medicine

Abstract

Purpose of Review

Recent Findings

Summary

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Other articles of this Issue 6/2024

Polyvascular disease: a serious situation

Use of Virtual Reality and 3D Models in Contemporary Practice of Cardiology

Improving outcomes in peripheral artery disease

Chagas Cardiomyopathy and Myocardial Sympathetic Denervation

Right Ventricle-Pulmonary Artery Coupling in Patients Undergoing Cardiac Interventions

Impact of Social Determinants of Health on Outcomes for Patients with Adult Congenital Heart Disease

2024 ESC Congress

Noise pollution dangerous for heart health

Post-TAVI follow up: deploying virtual assistants

Antihypertensives: more effective at morning or night?

Low Lp(a) levels unlikely to increase the risk of diabetes

» View more highlights on the 2024 ESC Congress hub page

A quick guide to ECGs

Keynote webinar | Spotlight on medication adherence