AI Medical Compendium Journal:
European heart journal. Digital health

Showing 1 to 10 of 16 articles

Artificial intelligence-based identification of left ventricular systolic dysfunction from 12-lead electrocardiograms: external validation and advanced application of an existing model.

European heart journal. Digital health
AIMS: The diagnostic application of artificial intelligence (AI)-based models to detect cardiovascular diseases from electrocardiograms (ECGs) evolves, and promising results were reported. However, external validation is not available for all publish...

Machine learning-based gait analysis to predict clinical frailty scale in elderly patients with heart failure.

European heart journal. Digital health
AIMS: Although frailty assessment is recommended for guiding treatment strategies and outcome prediction in elderly patients with heart failure (HF), most frailty scales are subjective, and the scores vary among raters. We sought to develop a machine...

Nurse-led home-based detection of cardiac dysfunction by ultrasound: results of the CUMIN pilot study.

European heart journal. Digital health
AIMS: Access to echocardiography is a significant barrier to heart failure (HF) care in many low- and middle-income countries. In this study, we hypothesized that an artificial intelligence (AI)-enhanced point-of-care ultrasound (POCUS) device could ...

Artificial intelligence-enhanced electrocardiogram for arrhythmogenic right ventricular cardiomyopathy detection.

European heart journal. Digital health
AIMS: ECG abnormalities are often the first signs of arrhythmogenic right ventricular cardiomyopathy (ARVC) and we hypothesized that an artificial intelligence (AI)-enhanced ECG could help identify patients with ARVC and serve as a valuable disease-d...

International evaluation of an artificial intelligence-powered electrocardiogram model detecting acute coronary occlusion myocardial infarction.

European heart journal. Digital health
AIMS: A majority of acute coronary syndromes (ACS) present without typical ST elevation. One-third of non-ST-elevation myocardial infarction (NSTEMI) patients have an acutely occluded culprit coronary artery [occlusion myocardial infarction (OMI)], l...

Development and internal validation of machine learning-based models and external validation of existing risk scores for outcome prediction in patients with ischaemic stroke.

European heart journal. Digital health
AIMS: We developed new machine learning (ML) models and externally validated existing statistical models [ischaemic stroke predictive risk score (iScore) and totalled health risks in vascular events (THRIVE) scores] for predicting the composite of re...

External validation of a deep learning algorithm for automated echocardiographic strain measurements.

European heart journal. Digital health
AIMS: Echocardiographic strain imaging reflects myocardial deformation and is a sensitive measure of cardiac function and wall-motion abnormalities. Deep learning (DL) algorithms could automate the interpretation of echocardiographic strain imaging.

Population data-based federated machine learning improves automated echocardiographic quantification of cardiac structure and function: the project.

European heart journal. Digital health
AIMS: Machine-learning (ML)-based automated measurement of echocardiography images emerges as an option to reduce observer variability. The objective of the study is to improve the accuracy of a pre-existing automated reading tool ('original detector...

Automatic triage of twelve-lead electrocardiograms using deep convolutional neural networks: a first implementation study.

European heart journal. Digital health
AIMS: Expert knowledge to correctly interpret electrocardiograms (ECGs) is not always readily available. An artificial intelligence (AI)-based triage algorithm (DELTAnet), able to support physicians in ECG prioritization, could help reduce current lo...