Proof

Ultromics is increasing the impact of echocardiography through real-world evidence and peer-reviewed publications. Discover publications, case studies, whitepapers, and more.

Publications

Publication

Utility of an Automated Artificial Intelligence Echocardiography Software in Risk Stratification of Hospitalized COVID-19 Patients

Publication

Human vs Artificial Intelligence-Based Echocardiography Analysis as Predictor of Outcomes (WASE-COVID)

Publication

Vendor Comparison of EchoGo with Competitor1A using the UK EVAREST Study.

Publication

WASE I: Echocardiography predicts death in patients with acute COVID-19 infection: The World Alliance Societies of Echocardiography (WASE-COVID) study.

Publication

WASE II: Ventricular changes in patients with acute COVID-19 infection: follow-up of The World Alliance Societies of Echocardiography (WASE-COVID) study.

Publication

Automated echocardiographic detection of severe coronary artery disease using artificial intelligence.

Publication

Ultrasound video transformers for cardiac ejection fraction estimation.

Publication

Contrastive learning for view classification of echocardiograms.

Conference posters

Poster

Novel Deep Learning Model for the Detection of Cardiac Amyloidosis: A Pilot Reader Study

Poster

Automated Echocardiographic Detection of HFpEF using AI

Poster

Comparison of clinical algorithms and artificial intelligence applied to an echocardiogram to categorize risk of heart failure with preserved ejection fraction (HFpEF)

Poster

Can Left Ventricular Rotational Function Compensate for Marked Impairment in Longitudinal Strain in Early Cardiac Amyloidosis?

Poster

Automated Analysis of Segmental Longitudinal Strain in Ischemic Heart Disease

Poster

Quantification of left ventricular regional wall motion: novel imaging features to predict coronary artery disease.

Poster

Fully automated strain analysis at rest and peak stress during standard and contrast enhanced stress echocardiography.

Poster

Coronary artery disease prediction from resting echocardiograms using novel imaging biomarkers.

Poster

Fully automated quantification of contrast and non-contrast echocardiograms eliminates inter-operator variability.

Poster

AI enabled global longitudinal strain quantification in hospitalized COVID-19 patients with myocardial injury.

Poster

Basal oriented disks in simpson’s rule improves precision in volume estimations.

Poster

Estimating heart rate in echocardiography patients where ECG monitoring was not performed.

Poster

Fully automated left ventricular ejection fraction and global longitudinal strain predicts obstructive coronary artery disease in patients undergoing stress echocardiography: A multi-centre study.

Poster

Fully automated quantification of LV regional wall motion from echocardiograms to detect myocardial infarction.

Poster

Automated contouring of non-contrast enhanced echocardiograms result in similar estimates of left ventricular function to manually contoured contrast enhanced images in chemotherapy patients.

Proof

Publications

Utility of an Automated Artificial Intelligence Echocardiography Software in Risk Stratification of Hospitalized COVID-19 Patients

Human vs Artificial Intelligence-Based Echocardiography Analysis as Predictor of Outcomes (WASE-COVID)

Vendor Comparison of EchoGo with Competitor1A using the UK EVAREST Study.

WASE I: Echocardiography predicts death in patients with acute COVID-19 infection: The World Alliance Societies of Echocardiography (WASE-COVID) study.

WASE II: Ventricular changes in patients with acute COVID-19 infection: follow-up of The World Alliance Societies of Echocardiography (WASE-COVID) study.

Automated echocardiographic detection of severe coronary artery disease using artificial intelligence.

Ultrasound video transformers for cardiac ejection fraction estimation.

Contrastive learning for view classification of echocardiograms.

Conference posters

Novel Deep Learning Model for the Detection of Cardiac Amyloidosis: A Pilot Reader Study

Automated Echocardiographic Detection of HFpEF using AI

Comparison of clinical algorithms and artificial intelligence applied to an echocardiogram to categorize risk of heart failure with preserved ejection fraction (HFpEF)

Can Left Ventricular Rotational Function Compensate for Marked Impairment ​in Longitudinal Strain in Early Cardiac Amyloidosis?

Automated Analysis of Segmental Longitudinal Strain in Ischemic Heart Disease

Quantification of left ventricular regional wall motion: novel imaging features to predict coronary artery disease.

Fully automated strain analysis at rest and peak stress during standard and contrast enhanced stress echocardiography.

Coronary artery disease prediction from resting echocardiograms using novel imaging biomarkers.

Fully automated quantification of contrast and non-contrast echocardiograms eliminates inter-operator variability.

AI enabled global longitudinal strain quantification in hospitalized COVID-19 patients with myocardial injury.

Basal oriented disks in simpson’s rule improves precision in volume estimations.

Estimating heart rate in echocardiography patients where ECG monitoring was not performed.

Fully automated left ventricular ejection fraction and global longitudinal strain predicts obstructive coronary artery disease in patients undergoing stress echocardiography: A multi-centre study.

Fully automated quantification of LV regional wall motion from echocardiograms to detect myocardial infarction.

Automated contouring of non-contrast enhanced echocardiograms result in similar estimates of left ventricular function to manually contoured contrast enhanced images in chemotherapy patients.

See EchoGo in action

Can Left Ventricular Rotational Function Compensate for Marked Impairment in Longitudinal Strain in Early Cardiac Amyloidosis?