AI Echo For Heart Failure

New research led by the University of Dundee, demonstrated the feasibility of AI to automatically identify and classify patients with heart failure from archived echocardiographic images with software.

AI for Contrast Echo

A study conducted at Christ Hospital Health Network and presented at ACC.24 showed good to excellent agreement between AI and experts assessments of LV volumes and ejection fraction in contrast echocardiograms.

AI for Contrast Echo

Evaluating the performance of automated deep learning algorithms for measurement of echo estimators of invasively measured PCWP.

AI Echo Productivity echocardiographic analysis led to a 70% reduction in measurement and report creation time compared to manual methods, as published in the Journal of Echocardiography.

AI Hypertension

Published in Nature Hypertension Research, this study used to support healthcare workers in South Africa obtain LVH measurements despite limited training, hand-held sonography devices, difficult imaging conditions, and limited personal resources for analysis.

AI powered home ultrasound

The CUMIN study, published in European Heart Journal Digital Health, showcases the technical feasibility of AI-POCUS with an EchoNous Kosmos in the hands of novice nurses and opens new possibilities for redefining how we approach cardiac care, particularly in regions with limited resources. The fusion of AI, POCUS and nursing expertise holds the promise of…

AI powered home ultrasound

The first fully automated AI software with validated global longitudinal strain in patients with and without atrial fibrillation; plus regional strain validated in real-world datasets; plus accurate identification of patients with heart failure, as well as those with regional wall-motion abnormalities, published in the European Heart Journal’s Digital Health.

Heart Failure Advances

Remarkable recent advances have revolutionized the field of heart failure. Survival has improved among individuals with heart failure and a reduced ejection fraction, as published in Nature Medicine.

AI For Heart Failure Detection

AI to identify cases and classify types of heart failure (HFpEF or HFrEF) from routine EHR surveillance, published in the Journal of Cardiac Failure.

AI Echo Aortic Stenosis

Aortic stenosis published in JASE. First study of its kind demonstrating the capacity of AI Echo to accurately quantify AoS severity with zero human input beyond image acquisition. See the results and the video.

AI Mortality Prediction

AI echo mortality prediction published in eBioMedicine. Echo can facilitate risk stratification, comparable in performance to established risk scores and correlated with patient’s quality of life measures. Read the publication.

AI Cardiac Ultrasound

AI-enabled, home-based cardiac care by nurses – abstract presented at the ESC Heart Failure Congress 2023. AI point-of-care ultrasound can improve access, enabling novice nurses to perform cardiac screening in patients’ homes. Download the results.

AI Echo For Mitral Regurgitation

AI-based MR severity grading presentation at EACVI 2023. Grading MR severity is essential due to high mortality. We’ve built an automated, machine learning based, multiparametric approach. Download the results.

AI Automation For Cardiac Amyloidosis

AI echo for cardiac amyloidosis. ATTR-CM is an ultimately fatal cause of heart failure. Manual analysis is slow and highly variable. We showed that automated AI echo can identify predictors of mortality. View the poster.

AI Automation For Strain Imaging

Strain is a sensitive measure of cardiac function, but clinical application remains limited due to expertise requirements and high variability. We showed AI Echo can automate generation and interpretation of strain. See the results.

AI Echo White Paper

A formal white paper on how to democratize echocardiography with augmented intelligence. Download the white paper.

Point Of Care Ai Assisted Novice Echocardiography

AI echo reports with AI Point-of-Care ultrasound enable novices to perform heart failure screening

AI Echocardiography

AI interpretation of echocardiograms – a formal validation of echo analysis software published in Nature Communications. Download the study.

Fully automated AI based echo strain analysis software

Echo Strain AI – validation of AI auto strain AI-assisted echocardiography presented at the AHA Scientific Sessions

Automated AI echo interpretation of systolic and diastolic function in a multicohort study

AI echo reports – automated echo diagnosis support for interpretation of systolic and diastolic function published in The Lancet Digital Health

AI echo - AI for Echocardiography Diagnosis Support

AI echo disease detection at scale – University of Dundee poster on the detection and diagnosis of patients with heart failure from electronic health records

AI POCUS - AI Point-of-Care Ultrasound for heart failure screening

JASE publication on AI Point-of-care Ultrasound with Continuous-Wave Doppler Capability to evaluate aortic stenosis

AI POCUS - AI Point-of-Care Ultrasound for heart failure screening

Machine learning for diastology and heart failure with preserved ejection fraction – editorial published in JASE

Cardiac imaging with AI - machine learning in echocardiography validation

Deep learning in echocardiography – an automated AI echo workflow validation presented at EuroEcho

The Lancet Women and Cardiovascular Disease Commission

Cardiovascular disease is the leading cause of death in women. Reducing the global burden by 2030