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.
November
14
2022
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Nature Medicine
Prospective evaluation of smartwatch-enabled detection of left ventricular dysfunction
Although artificial intelligence (AI) algorithms have been shown to be capable of identifying cardiac dysfunction, defined as ejection fraction (EF) ≤ 40%, from 12-lead electrocardiograms (ECGs), identification of cardiac dysfunction…
November
13
2022
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American Journal of Preventive Cardiology
Community-based participatory research application of an artificial intelligence-enhanced electrocardiogram for cardiovascular disease screening: A FAITH! Trial ancillary study
We conducted this study to evaluate the potential utility of an AI-based cardiovascular diseases (CVD) screening tool in an under-resourced African-American cohort, we reviewed the AI-enhanced electrocardiogram (ECG) data of…
November
01
2022
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Mayo Clinic Proceedings
Clinician Adoption of an Artificial Intelligence Algorithm to Detect Left Ventricular Systolic Dysfunction in Primary Care.
In this study, we aimed to compare the clinicians’ characteristics of “high adopters” and “low adopters” of an artificial intelligence (AI)–enabled electrocardiogram (ECG) algorithm that alerted for possible low left…
October
21
2022
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Cardiovascular Digital Health Journal
Tandem deep learning and logistic regression models to optimize hypertrophic cardiomyopathy detection in routine clinical practice
An electrocardiogram (ECG)-based artificial intelligence (AI) algorithm has shown good performance in detecting hypertrophic cardiomyopathy (HCM). However, its application in routine clinical practice may be challenging due to the low…
October
14
2022
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JMIR AI
Provider Perspectives on Artificial Intelligence-Guided Screening for Low Ejection Fraction in Primary Care: Qualitative Study
In this study, we aimed to describe provider perspectives on the adoption of an AI-enabled screening tool in primary care to inform effective integration and sustained use. A qualitative study…
September
27
2022
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The Lancet
Artificial intelligence-guided screening for atrial fibrillation using electrocardiogram during sinus rhythm: a prospective non-randomised interventional trial
Background: Previous atrial fibrillation screening trials have highlighted the need for more targeted approaches. We did a pragmatic study to evaluate the effectiveness of an artificial intelligence (AI) algorithm-guided targeted…
September
27
2022
{post_date: F d, Y}
Cardiovascular Digital Health Journal
Emerging role of artificial intelligence in cardiac electrophysiology
Key Findings: • Artificial Intelligence and machine learning have significantly impacted the field of cardiac electrophysiology. • Application of AI to EKG, data from wearables and smart devices can provide…
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…
September
01
2022
{post_date: F d, Y}
Current Cardiology Reports
Artificial Intelligence Applied to Cardiomyopathies: Is It Time for Clinical Application?
Many studies have been undertaken in recent years on cardiomyopathy screening especially using AI-enhanced electrocardiography (ECG). While the implementation of AI in the diagnosis and treatment of cardiomyopathies is still…
August
29
2022
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Nature
Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes
Artificial Intelligence (AI) based approaches can now use electrocardiograms (ECGs) to provide expert-level performance in detecting heart abnormalities and diagnosing disease. Additionally, patient age predicted from ECGs by AI models…