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
September 16, 2022
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
August 08, 2022
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
May 22, 2022
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
May 17, 2022
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
January 04, 2022
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
December 06, 2021
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
June 09, 2021
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
June 08, 2021
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
May 05, 2021
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
April 30, 2021
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…