AI/ML Innovations Inc. announces the launch of their Neural Net as a Service Platform, providing healthcare providers and researchers with access to advanced neural…
Browsing: ECG
A deep learning model using transthoracic echocardiograms (TTEs) can accurately predict patients with active or occult atrial fibrillation (AF). The model was trained on…
This article discusses the use of a multi-task deep learning model to detect multiple sclerosis (MS) and classify left ventricular ejection fraction (LVEF) using…
This article presents a framework for predicting the occurrence of atrial fibrillation (AF) using a single-lead ECG obtained from a chest patch. The framework…
Artificial intelligence (AI) and its subsets, such as machine learning, neural networks, and deep learning, have the potential to revolutionize the medical field. AI…
Researchers from ITMO’s Research Center “Strong AI in Industry” have developed an algorithm that can detect a heart attack in a single-lead ECG in…
This article discusses the use of machine learning approaches to predict prodromal Parkinson’s Disease (PD) using clinical variables and standard 10-second electrocardiogram (ECG) recordings.…
Mount Sinai’s AI model HeartBEiT improves the accuracy and detail of ECG diagnostics, even in rare conditions with limited data. It interprets the ECG…
Mount Sinai researchers have developed an AI model, HeartBEiT, for electrocardiogram (ECG) analysis that interprets ECGs as language. This approach can improve the accuracy…
Machine learning (ML) methods for the analysis of electrocardiography (ECG) data are gaining importance, and are supported by the release of large public datasets.…