| Delineation of the electrocardiogram with a mixed-quality-annotations dataset using convolutional neural networks G Jimenez-Perez, A Alcaine, O Camara Scientific reports 11 (1), 863, 2021 | 57* | 2021 |
| U-Net architecture for the automatic detection and delineation of the electrocardiogram G Jimenez-Perez, A Alcaine, O Camara 2019 Computing in Cardiology (CinC), Page 1-Page 4, 2019 | 41 | 2019 |
| Deep learning surrogate of computational fluid dynamics for thrombus formation risk in the left atrial appendage X Morales, J Mill, KA Juhl, A Olivares, G Jimenez-Perez, RR Paulsen, ... Statistical Atlases and Computational Models of the Heart. Multi-Sequence …, 2020 | 24 | 2020 |
| Generalizing electrocardiogram delineation--Training convolutional neural networks with synthetic data augmentation G Jimenez-Perez, J Acosta, A Alcaine, O Camara arXiv preprint arXiv:2111.12996, 2021 | 12 | 2021 |
| Training machine learning models with synthetic data improves the prediction of ventricular origin in outflow tract ventricular arrhythmias R Doste, M Lozano, G Jimenez-Perez, L Mont, A Berruezo, D Penela, ... Frontiers in Physiology 13, 909372, 2022 | 10 | 2022 |
| Artificial intelligence for detection of ventricular oversensing: Machine learning approaches for noise detection within nonsustained ventricular tachycardia episodes remotely … M Strik, B Sacristan, P Bordachar, J Duchateau, R Eschalier, P Mondoly, ... Heart Rhythm 20 (10), 1378-1384, 2023 | 7 | 2023 |
| Towards assisted electrocardiogram interpretation using an AI-enabled Augmented Reality headset P Lampreave, G Jimenez-Perez, I Sanz, A Gomez, O Camara Computer Methods in Biomechanics and Biomedical Engineering: Imaging …, 2021 | 6 | 2021 |
| Unsupervised machine learning exploration of morphological and haemodynamic indices to predict thrombus formation in the left atrial appendage M Saiz-Vivó, J Mill, J Harrison, G Jimenez-Pérez, B Legghe, X Iriart, ... International Workshop on Statistical Atlases and Computational Models of …, 2022 | 4 | 2022 |
| Machine learning-based phenotyping and risk assessment of hypertrophic cardiomyopathy-linking ECGs, morphology and genotypes G Jimenez-Perez, F Loncaric, PM Marti Castellote, M Ramos Jovani, ... European Heart Journal-Cardiovascular Imaging 23 (Supplement_1), jeab289. 431, 2022 | 4 | 2022 |
| Latent Diffusion Models with Image-Derived Annotations for Enhanced AI-Assisted Cancer Diagnosis in Histopathology P Osorio, G Jimenez-Perez, J Montalt-Tordera, J Hooge, ... Diagnostics 14 (13), 2024 | 3 | 2024 |
| Benchmark of deep learning algorithms for the automatic screening in electrocardiograms transmitted by implantable cardiac devices N Gassa, B Sacristan, N Zemzemi, M Laborde, JG Oliver, CM Perabla, ... 2021 Computing in Cardiology (CinC) 48, 1-4, 2021 | 3 | 2021 |
| Mobile app for the digitization and deep-learning-based classification of electrocardiogram printed records A Isabel, G Jimenez-Perez, O Camara, E Silva 2021 Computing in Cardiology (CinC) 48, 1-4, 2021 | 3 | 2021 |
| Machine learning to automatically detect anatomical landmarks on phase-contrast enhanced magnetic resonance angiography A Guala, M Mejia Cordova, X Morales, G Jimenez-Perez, L Dux-Santoy, ... European Heart Journal-Cardiovascular Imaging 22 (Supplement_2), jeab090. 122, 2021 | 3 | 2021 |
| Reinforcement machine learning-based aortic anatomical landmarks detection from phase-contrast enhanced magnetic resonance angiography M Mejia Cordova, A Guala, X Morales, G Jimenez-Perez, L Dux-Santoy, ... European Heart Journal-Cardiovascular Imaging 22 (Supplement_1), jeaa356. 286, 2021 | 3 | 2021 |
| Generalising electrocardiogram detection and delineation: training convolutional neural networks with synthetic data augmentation G Jimenez-Perez, J Acosta, A Alcaine, O Camara Frontiers in Cardiovascular Medicine 11, 1341786, 2024 | | 2024 |
| DiNO-Diffusion. Scaling Medical Diffusion via Self-Supervised Pre-Training G Jimenez-Perez, P Osorio, J Cersovsky, J Montalt-Tordera, J Hooge, ... arXiv preprint arXiv:2407.11594, 2024 | | 2024 |
| Delineation of intracavitary electrograms for the automatic quantification of decrement-evoked potentials in the coronary sinus with deep-learning techniques G Jimenez-Perez, J Acosta, ÁJ Bocanegra-Pérez, E Arana-Rueda, ... Frontiers in Physiology 15, 1331852, 2024 | | 2024 |
| Automatic and interpretable prediction of the site of origin in outflow tract ventricular arrhythmias: machine learning integrating electrocardiograms and clinical data ÁJ Bocanegra-Pérez, G Piella, R Sebastian, G Jimenez-Perez, ... Frontiers in Cardiovascular Medicine 11, 1353096, 2024 | | 2024 |
| Automatic Prediction of the Origin in Outflow Tract Ventricular Arrhythmias with Machine Learning Combining Clinical Data and Electrocardiogram Analysis ÁJ Bocanegra, D Penela, R Sebastian, G Jimenez-Perez, A Saglietto, ... 2023 Computing in Cardiology (CinC) 50, 1-4, 2023 | | 2023 |
| Unsupervised Machine Learning Exploration of Morphological and Haemodynamic Indices to Predict Thrombus Formation in the Left Atrial Appendage G Jimenez-Pérez, B Legghe, X Iriart, H Cochet, G Piella, M Sermesant, ... Statistical Atlases and Computational Models of the Heart. Regular and …, 2023 | | 2023 |
