Ali Rababah
Orcid: 0000-0002-2078-635X
According to our database1,
Ali Rababah
authored at least 16 papers
between 2018 and 2022.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2022
Machine learning and the electrocardiogram over two decades: Time series and meta-analysis of the algorithms, evaluation metrics and applications.
Artif. Intell. Medicine, 2022
Proceedings of the Computing in Cardiology, 2022
Influence of the Training Set Size on the Subject-to-Subject Variability of the Estimation Performance of Linear ECG-Lead Transformations.
Proceedings of the Computing in Cardiology, 2022
Effect of Segmentation Uncertainty on the ECGI Inverse Problem Solution and Source Localization.
Proceedings of the Computing in Cardiology, 2022
2021
The effect of interpolating low amplitude leads on the inverse reconstruction of cardiac electrical activity.
Comput. Biol. Medicine, 2021
Coefficients for the Derivation of an ST Sensitive Patch Based Lead System from the 12 Lead Electrocardiogram.
Proceedings of the Computing in Cardiology, CinC 2021, Brno, 2021
Estimating the Minimal Size of Training Datasets Required for the Development of Linear ECG-Lead Transformations.
Proceedings of the Computing in Cardiology, CinC 2021, Brno, 2021
Proceedings of the Computing in Cardiology, CinC 2021, Brno, 2021
2020
Coefficients for the Derivation of Posterior and Right Sided Chest Leads From the 12-lead Electrocardiogram.
Proceedings of the Computing in Cardiology, 2020
Regression or Pseudo-Inverse - Which Method Should be Preferred When Developing Inverse Linear ECG-Lead Transformations?
Proceedings of the Computing in Cardiology, 2020
Towards Explainable Artificial Intelligence and Explanation User Interfaces to Open the 'Black Box' of Automated ECG Interpretation.
Proceedings of the Advanced Visual Interfaces. Supporting Artificial Intelligence and Big Data Applications, 2020
2019
Interpolating Low Amplitude ECG Signals Combined with Filtering According to International Standards Improves Inverse Reconstruction of Cardiac Electrical Activity.
Proceedings of the Functional Imaging and Modeling of the Heart, 2019
Machine Learning Improves the Detection of Misplaced V1 and V2 Electrodes During 12-Lead Electrocardiogram Acquisition.
Proceedings of the 46th Computing in Cardiology, 2019
ST Changes Observed in Short Spaced Bipolar Leads Suitable for Patch Based Monitoring.
Proceedings of the 46th Computing in Cardiology, 2019
Proceedings of the 46th Computing in Cardiology, 2019
2018
An Adaptive Laplacian Based Interpolation Algorithm for Noise Reduction in Body Surface Potential Maps.
Proceedings of the Computing in Cardiology, 2018