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.
January
16
2026
January 16, 2026
JACC
Multisite, External Validation of an AI-Enabled ECG Algorithm for Detection of Low Ejection Fraction
Abstract Background: Low left ventricular ejection fraction (LEF) can progress undiagnosed. Artificial intelligence–based electrocardiogram (ECG-AI) screening may provide a scalable means to detect LEF.Objectives: The purpose of this study was…
November
12
2025
November 12, 2025
JACC
Predicting Heart Failure From 12-Lead ECGs Using AI: A HeartShare/AMP-HF Pooled Cohort Analysis
Abstract Background: Artificial intelligence applied to electrocardiograms (ECG-AI) offers a scalable approach to identify individuals at risk for heart failure (HF) and guide preventive interventions. Objective: The purpose of this study was…
August
25
2025
August 25, 2025
CJASN
Validation of Noninvasive Detection of Hyperkalemia by Artificial Intelligence-Enhanced Electrocardiography in High Acuity Settings
Abstract: Key Points • Measuring blood potassium has always required access to blood. The surface electrocardiogram, analyzed using an artificial intelligence algorithm, can detect hyperkalemia bloodlessly. • The artificial intelligence-analyzed…
October
25
2024
October 25, 2024
Mayo Clinic Proceedings: Digital Health
Cost-Effectiveness of AI-Enabled Electrocardiograms for Early Detection of Low Ejection Fraction: A Secondary Analysis of the EAGLE Trial
Objective: To investigate the cost-effectiveness of using artificial intelligence (AI) to screen for low ejection fraction (EF) in routine clinical practice using a pragmatic randomized controlled trial (RCT). Participants &…
October
14
2024
October 14, 2024
European Heart Journal
Artificial Intelligence Evaluation of Electrocardiographic Characteristics and Interval Changes in Transgender Patients on Gender-Affirming Hormone Therapy
Background: Gender-affirming hormone therapy (GAHT) is used by some transgender individuals (TG), who comprise 1.4% of US population. However, the effects of GAHT on ECG remain unknown. Objective To assess…
September
27
2024
September 27, 2024
ScienceDirect
Artificial Intelligence-Enhanced Electrocardiography Identifies Patients With Normal Ejection Fraction at Risk of Worse Outcomes
Abstract: Background An artificial intelligence (AI)-based electrocardiogram (ECG) model identifies patients with a higher likelihood of low ejection fraction (EF). Patients with an abnormal AI-ECG score but normal EF (false…
September
01
2024
September 01, 2024
Nature Medicine
Artificial intelligence guided screening for cardiomyopathies in an obstetric population: a pragmatic randomized clinical trial
Nigeria has the highest reported incidence of peripartum cardiomyopathy worldwide. This open-label, pragmatic clinical trial randomized pregnant and postpartum women to usual care or artificial intelligence (AI)-guided screening to assess…
August
30
2024
August 30, 2024
Wiley Online Library
Predictors of mortality by an artificial intelligence enhanced electrocardiogram model for cardiac amyloidosis
Aims: We aim to determine if our previously validated, diagnostic artificial intelligence (AI) electrocardiogram (ECG) model is prognostic for survival among patients with cardiac amyloidosis (CA). Methods: A total of…
January
06
2024
January 06, 2024
Nature Medicine
Artificial intelligence-enabled ECG for left ventricular diastolic function and filling pressure
Assessment of left ventricular diastolic function plays a major role in the diagnosis and prognosis of cardiac diseases, including heart failure with preserved ejection fraction. We aimed to develop an…
October
02
2023
October 02, 2023
JACC
Patient-Level Artificial Intelligence-Enhanced Electrocardiography in Hypertrophic Cardiomyopathy: Longitudinal Treatment and Clinical Biomarker Correlations
Background: Artificial intelligence (AI) applied to 12-lead electrocardiographs (ECGs) can detect hypertrophic cardiomyopathy (HCM). Objectives The purpose of this study was to determine if AI-enhanced ECG (AI-ECG) can track longitudinal…