Predicting survival from large echocardiography and electronic health record datasets: optimization with machine learning
Objectives: The goal of this study was to use machine learning to more accurately predict
survival after echocardiography. Background: Predicting patient outcomes (eg, survival) …
survival after echocardiography. Background: Predicting patient outcomes (eg, survival) …
rECHOmmend: an ECG-based machine learning approach for identifying patients at increased risk of undiagnosed structural heart disease detectable by …
Background: Timely diagnosis of structural heart disease improves patient outcomes, yet
many remain underdiagnosed. While population screening with echocardiography is …
many remain underdiagnosed. While population screening with echocardiography is …
Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortality
AE Ulloa Cerna, L Jing, CW Good… - Nature Biomedical …, 2021 - nature.com
Abstract Machine learning promises to assist physicians with predictions of mortality and of
other future clinical events by learning complex patterns from historical data, such as …
other future clinical events by learning complex patterns from historical data, such as …
Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease
Prognostic modelling is important in clinical practice and epidemiology for patient
management and research. Electronic health records (EHR) provide large quantities of data …
management and research. Electronic health records (EHR) provide large quantities of data …
Deep learning for predicting in‐hospital mortality among heart disease patients based on echocardiography
Background Heart disease (HD) is the leading cause of global death; there are several
mortality prediction models of HD for identifying critically‐ill patients and for guiding decision …
mortality prediction models of HD for identifying critically‐ill patients and for guiding decision …
Automation, machine learning, and artificial intelligence in echocardiography: a brave new world
Automation, machine learning, and artificial intelligence (AI) are changing the landscape of
echocardiography providing complimentary tools to physicians to enhance patient care …
echocardiography providing complimentary tools to physicians to enhance patient care …
Machine learning in cardiovascular medicine: are we there yet?
Artificial intelligence (AI) broadly refers to analytical algorithms that iteratively learn from
data, allowing computers to find hidden insights without being explicitly programmed where …
data, allowing computers to find hidden insights without being explicitly programmed where …
Artificial intelligence and echocardiography
M Alsharqi, WJ Woodward, JA Mumith… - Echo Research & …, 2018 - Springer
Echocardiography plays a crucial role in the diagnosis and management of cardiovascular
disease. However, interpretation remains largely reliant on the subjective expertise of the …
disease. However, interpretation remains largely reliant on the subjective expertise of the …
Fully automated echocardiogram interpretation in clinical practice: feasibility and diagnostic accuracy
Background: Automated cardiac image interpretation has the potential to transform clinical
practice in multiple ways, including enabling serial assessment of cardiac function by …
practice in multiple ways, including enabling serial assessment of cardiac function by …
Automated echocardiographic detection of severe coronary artery disease using artificial intelligence
Objectives The purpose of this study was to establish whether an artificially intelligent (AI)
system can be developed to automate stress echocardiography analysis and support …
system can be developed to automate stress echocardiography analysis and support …