Jul 23, 2023 · We present RAST, an approach able at identifying the same abnormalities but on a highly compressed ECG signal.

After obtaining the medical data, an analysis may be carried out using an Artificial Intelligence (AI)-based data transformation and interpretation approach, [ ...

ST-Segment Anomalies Detection from Compressed Sensing Based ECG Data by Means of Machine Learning. July 2023. DOI:10.1007/978-3-031-38854-5_13. In book ...

Previous work introduced AI-based approaches for automatically detecting hearth-related anomalies based on the electrocardiographic (ECG) signal. However, most ...

ST-Segment Anomalies Detection from Compressed Sensing Based ECG Data by Means of Machine Learning ... Authors: Giovanni Rosa; Marco Russodivito; Gennaro Laudato ...

ST-Segment Anomalies Detection from Compressed Sensing Based ECG Data by Means of Machine Learning. Rosa, Giovanni;Russodivito, Marco;Laudato, Gennaro ...

ST-Segment Anomalies Detection from Compressed Sensing Based ECG Data by Means of Machine Learning. G Rosa, M Russodivito, G Laudato, AR Colavita, L De Vito ...

AI algorithms can help clinicians in the following areas: (1) interpretation and detection of arrhythmias, ST-segment changes, QT prolongation, and other ECG ...

This work is based on the application of signal processing and artificial intelligence to the heart signal known as the ECG (Electrocardiogram). Coronary heart ...

In this study, we implemented a number of deep neural networks on a publicly available dataset of PTB-XL of ECG signals for the detection of cardiac disorders.