Ali Rababah

Orcid: 0000-0002-2078-635X

According to our database1, Ali Rababah authored at least 16 papers between 2018 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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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

The Effect of Segmentation Variability in Forward ECG Simulation.
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

Impact of baseline drift removal on ECG beat classification and alignment.
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

Effects of Interpolation on the Inverse Problem of Electrocardiography.
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


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