Samuel Ruipérez-Campillo
Orcid: 0000-0002-5425-4175
According to our database1,
Samuel Ruipérez-Campillo
authored at least 18 papers
between 2020 and 2024.
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Bibliography
2024
Novel synchronization method for vectorcardiogram reconstruction from ECG printouts: A comprehensive validation approach.
Biomed. Signal Process. Control., 2024
Can Generative AI Learn Physiological Waveform Morphologies? A Study on Denoising Intracardiac Signals in Ischemic Cardiomyopathy.
Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024
EEG Tensorization Enhances CNN-Based Outcome Classification in Comatose Patients Following a Cardiac Arrest.
Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024
2023
Performance assessment of electrode configurations for the estimation of omnipolar electrograms from high density arrays.
Comput. Biol. Medicine, March, 2023
Mini Peltier Cell Array System for the Generation of Controlled Local Epicardial Heterogeneities.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023
Robust Framework for Medical Time Series Classification and Application to Real Scenarios in Modern Bioengineering.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023
Assessment of the Interelectrode Distance Effect over the Omnipole with High Multielectrode Arrays.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023
Synchronization of Conventional Electrocardiogram Recordings for Accurate Vectorcardiography Reconstruction.
Proceedings of the Computing in Cardiology, 2023
Defining the Predictive Ceiling of Electrogram Features Alone for Predicting Outcomes From Atrial Fibrillation Ablation.
Proceedings of the Computing in Cardiology, 2023
Heterogeneity Quantification of Electrophysiological Signal Propagation in High-Density Multielectrode Recordings.
Proceedings of the Computing in Cardiology, 2023
Proceedings of the Computing in Cardiology, 2023
2022
Classification of Atrial Tachycardia Types Using Dimensional Transforms of ECG Signals and Machine Learning.
Proceedings of the Computing in Cardiology, 2022
Deep Learning for Ventricular Arrhythmia Prediction Using Fibrosis Segmentations on Cardiac MRI Data.
Proceedings of the Computing in Cardiology, 2022
Weakly-Supervised Deep Learning for Left Ventricle Fibrosis Segmentation in Cardiac MRI Using Image-Level Labels.
Proceedings of the Computing in Cardiology, 2022
Autocorrelation Function for Predicting Arrhythmic Recurrences in Patients Undergoing Persistent Atrial Fibrillation Ablation.
Proceedings of the Computing in Cardiology, 2022
Proceedings of the Computing in Cardiology, 2022
2021
Non-invasive characterisation of macroreentrant atrial tachycardia types from a vectorcardiographic approach with the slow conduction region as a cornerstone.
Comput. Methods Programs Biomed., 2021
2020
Slow Conduction Regions as a Valuable Vectorcardiographic Parameter for the Non-Invasive Identification of Atrial Flutter Types.
Proceedings of the Computing in Cardiology, 2020