Cargando…
A Systematic Survey of Data Augmentation of ECG Signals for AI Applications
AI techniques have recently been put under the spotlight for analyzing electrocardiograms (ECGs). However, the performance of AI-based models relies on the accumulation of large-scale labeled datasets, which is challenging. To increase the performance of AI-based models, data augmentation (DA) strat...
Autores principales: | Rahman, Md Moklesur, Rivolta, Massimo Walter, Badilini, Fabio, Sassi, Roberto |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256074/ https://www.ncbi.nlm.nih.gov/pubmed/37299964 http://dx.doi.org/10.3390/s23115237 |
Ejemplares similares
-
ECG-iCOVIDNet: Interpretable AI model to identify changes in the ECG signals of post-COVID subjects
por: Agrawal, Amulya, et al.
Publicado: (2022) -
Machine Learning Using a Single-Lead ECG to Identify Patients With Atrial Fibrillation-Induced Heart Failure
por: Luongo, Giorgio, et al.
Publicado: (2022) -
Relationship Between Deceleration Morphology and Phase Rectified Signal Averaging-Based Parameters During Labor
por: Rivolta, Massimo W., et al.
Publicado: (2021) -
What is augmented analytics?: Powering your data with AI
por: LaPlante, Alice
Publicado: (2019) -
ECG Synthesis via Diffusion-Based State Space Augmented Transformer
por: Zama, Md Haider, et al.
Publicado: (2023)