Published Scientific Evidence
Anumana’s ECG-AI® technology is supported by one of the most extensive evidence bases in cardiovascular AI. This library provides direct access to our peer-reviewed validation studies and broader body of clinical research.
April
30
2021
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Poster @ American College of Cardiology (ACC) 2021
Artificial Intelligence Helps Identify Patients With Graves’ Disease At Risk For Atrial Fibrillation
BackgroundGraves' disease (GD) is known to be associated with atrial fibrillation (AF). Artificial intelligence (AI)-enabled ECGs using a convolutional neural network can identify the signature of silent AF. Whether the…
April
23
2021
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European Heart Journal
The 12-lead electrocardiogram as a biomarker of biological age
In a previous study, we demonstrated that a neural network is able to predict a person’s age from the electrocardiogram (ECG). However, some discrepancies were observed between ECG-derived and chronological…
March
21
2021
{post_date: F d, Y}
European Heart Journal
Electrocardiogram screening for aortic valve stenosis using artificial intelligence
Early detection of aortic stenosis (AS) is becoming increasingly important with a better outcome after aortic valve replacement in asymptomatic severe AS patients and a poor outcome in moderate AS.…
March
10
2021
{post_date: F d, Y}
Poster Abstract @ International Stroke Conference 2021
Artificial Intelligence Enabled-Electrocardiography for the Detection of Cerebral Infarcts in Patients With Atrial Fibrillation
BackgroundAtrial fibrillation (AF) is an established risk factor for ischemic stroke but can be paroxysmal and go undiagnosed. An artificial intelligence (AI)-enabled ECG acquired during normal sinus rhythm was recently…
February
01
2021
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Nature Medicine
Artificial intelligence-enhanced electrocardiography in cardiovascular disease management
The application of artificial intelligence (AI) to the electrocardiogram (ECG), a ubiquitous and standardized test, is an example of the ongoing transformative effect of AI on cardiovascular medicine. Although the…
February
01
2021
{post_date: F d, Y}
Nature Medicine
Artificial intelligence-enhanced electrocardiography in cardiovascular disease management
The application of artificial intelligence (AI) to the electrocardiogram (ECG), a ubiquitous and standardized test, is an example of the ongoing transformative effect of AI on cardiovascular medicine. Although the…
January
31
2021
{post_date: F d, Y}
Journal of the Americal College of Cardiology (JACC) / ACC.21
Detection Of Hypertrophic Cardiomyopathy By Artificial Intelligence-Enabled Electrocardiography In Children And Adolescents
Hypertrophic cardiomyopathy (HCM) is a cause of morbidity and sudden cardiac death in children and adolescents. There is currently no established screening approach for HCM. We recently developed an artificial…
January
02
2021
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International Journal of Cardiology
External validation of a deep learning electrocardiogram algorithm to detect ventricular dysfunction
ObjectiveTo validate a novel artificial-intelligence electrocardiogram algorithm (AI-ECG) to detect left ventricular systolic dysfunction (LVSD) in an external population.BackgroundLVSD, even when asymptomatic, confers increased morbidity and mortality. We recently derived…
November
25
2020
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European Heart Journal
The association of artificial intelligence-enabled electrocardiogram-derived age (physiologic age) with atherosclerotic cardiovascular events in the community
This study demonstrates that artificial intelligence interpretation of ECGs (AI-ECG) can estimate an individual's physiologic age and that the gap between AI-ECG and chronologic age (Age-Gap) is associated with increased…
November
12
2020
{post_date: F d, Y}
Circulation: Arrhythmia and Electrophysiology
Artificial Intelligence-Electrocardiography to Predict Incident Atrial Fibrillation
Background:An artificial intelligence (AI) algorithm applied to electrocardiography during sinus rhythm has recently been shown to detect concurrent episodic atrial fibrillation (AF). We sought to characterize the value of AI–enabled…