Published Scientific Evidence
Category: (Low Ejection Fraction)
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.
September
16
2022
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Mayo Clinic Proceedings
Electrocardiogram-Artificial Intelligence and Immune-Mediated Necrotizing Myopathy: Predicting Left Ventricular Dysfunction and Clinical Outcomes
This study was conducted to characterize the utility of an existing electrocardiogram (ECG)-artificial intelligence (AI) algorithm of left ventricular dysfunction (LVD) in immune-mediated necrotizing myopathy (IMNM). A retrospective cohort observational…
August
08
2022
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Intelligence-Based Medicine
Digitizing paper based ECG files to foster deep learning based analysis of existing clinical datasets: An exploratory analysis
Recently, we developed and validated a deep learning model for detecting left ventricular dysfunction based on a standard 12-lead ECG. However, this model largely depends on the availability of digital…
May
22
2022
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European Heart Journal
Automated Detection of Low Ejection Fraction from a One-lead Electrocardiogram: Application of an AI algorithm to an ECG-enabled Digital Stethoscope
ECG-enabled stethoscopes (ECG-Scope) acquire single lead ECGs during cardiac auscultation, and may facilitate real-time screening for pathologies not routinely identified by cardiac auscultation alone. Since we previously demonstrated an artificial…
May
17
2022
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European Heart Journal
Real-world performance, long-term efficacy, and absence of bias in the artificial intelligence enhanced electrocardiogram to detect left ventricular systolic dysfunction
We assessed the real-world performance of the artificial intelligence-enhanced electrocardiogram to detect left ventricular systolic dysfunction with respect to multiple patient and electrocardiogram variables to determine the algorithm’s long-term efficacy…
January
04
2022
{post_date: F d, Y}
The Lancet Digital Health
Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study
Most patients who have heart failure with a reduced ejection fraction, when left ventricular ejection fraction (LVEF) is 40% or lower, are diagnosed in hospital. This is despite previous presentations…
December
06
2021
{post_date: F d, Y}
PLOS
Left ventricular systolic dysfunction predicted by artificial intelligence using the electrocardiogram in Chagas disease patients-The SaMi-Trop cohort
Left ventricular systolic dysfunction (LVSD) in Chagas disease (ChD) is relatively common and its treatment using low-cost drugs can improve symptoms and reduce mortality. Recently, an artificial intelligence (AI)-enabled ECG…
June
09
2021
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Mayo Clinic Proceedings
Artificial Intelligence-Augmented Electrocardiogram Detection of Left Ventricular Systolic Dysfunction in the General Population
The goal of this study was to validate an AI-enabled ECG algorithm for the detection of preclinical left ventricular systolic dysfunction (LVSD) in a large community-based cohort. We found that…
June
08
2021
{post_date: F d, Y}
Mayo Clinic Proceedings
Cost Effectiveness of an Electrocardiographic Deep Learning Algorithm to Detect Asymptomatic Left Ventricular Dysfunction
We used decision analytic modeling to perform a cost-effectiveness analysis of the use of AI-ECG to screen for asymptomatic left ventricular dysfunction (ALVD) once at age 65 compared with no…
May
05
2021
{post_date: F d, Y}
Nature Medicine
Artificial intelligence-enabled electrocardiograms for identification of patients with low ejection fraction: a pragmatic, randomized clinical trial
We have conducted a pragmatic clinical trial aimed to assess whether an electrocardiogram (ECG)-based, artificial intelligence (AI)-powered clinical decision support tool enables early diagnosis of low ejection fraction (EF), a…
April
30
2021
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Poster @ American College of Cardiology (ACC) 2021
Validation Of An Artificial Intelligence Electrocardiogram Based Algorithm For The Detection Of Left Ventricular Systolic Dysfunction In Subjects With Chagas Disease
BackgroundChagas cardiomyopathy is a frequent and severe manifestation of Chagas disease (CD) and it is a leading cause of morbidity and death in South America. The dilated cardiomyopathy in CD…