| Offline training for memristor-based neural networks G Boquet, E Macias, A Morell, J Serrano, E Miranda, JL Vicario 2020 28th European Signal Processing Conference (EUSIPCO), 1547-1551, 2021 | 13 | 2021 |
| Knowledge extraction based on wavelets and DNN for classification of physiological signals: Arousals case E Macias, A Morell, J Serrano, JL Vicario 2018 Computing in Cardiology Conference (CinC) 45, 1-4, 2018 | 12 | 2018 |
| Novel Imputing Method and Deep Learning Techniques for Early Prediction of Sepsis in Intensive Care Units E Macias, G Boquet, J Serrano, JL Vicario, J Ibeas, A Morel Computing in Cardiology Conference (CinC) 46, 1, 2019 | 11 | 2019 |
| Mortality prediction enhancement in end-stage renal disease: A machine learning approach E Macias, A Morell, J Serrano, JL Vicario, J Ibeas Informatics in Medicine Unlocked 19, 100351, 2020 | 10 | 2020 |
| Theoretical tuning of the autoencoder bottleneck layer dimension: A mutual information-based algorithm G Boquet, E Macias, A Morell, J Serrano, JL Vicario 2020 28th European Signal Processing Conference (EUSIPCO), 1512-1516, 2021 | 6 | 2021 |
| MO463: machine learning-based prediction of mortality and risk factors in patients with chronic kidney disease developed with data from 10000 patients over 11 years J Ibeas, O Galles, N Monill, E Macias, A Morell, J Serrano, D Rexachs, ... Nephrology Dialysis Transplantation 37 (Supplement_3), gfac070. 077, 2022 | 2 | 2022 |
| Novel imputation method using average code from autoencoders in clinical data E Macias, J Serrano, JL Vicario, A Morell 2020 28th European Signal Processing Conference (EUSIPCO), 1576-1579, 2021 | 2 | 2021 |
| Sp689 renal failure and mortality: From evidence to artificial intelligence, change of paradigm? J Ibeas, E Macias, C Rubiella, A Morell, J Serrano, A Rodriguez-Jornet, ... Nephrology Dialysis Transplantation 34 (Supplement_1), gfz103. SP689, 2019 | 2 | 2019 |
| Novel imputing method for the early prediction of sepsis in icu using deep learning techniques E Macias, G Boquet, J Serrano, JL Vicario, J Ibeas, A Morell Computing in Cardiology, 2019 | 2 | 2019 |
| Transfer Learning Improving Predictive Mortality Models for Patients in End-Stage Renal Disease E Macias, J Lopez Vicario, J Serrano, J Ibeas, A Morell Electronics 11 (9), 1447, 2022 | 1 | 2022 |
| # 4640 PREDICTION OF CHRONIC KIDNEY DISEASE PROGRESSSION WITH ARTIFICIAL INTELLIGENCE: A CHALLENGE WITHIN OUR REACH O Galles, MC Rodríguez, R Suppi, E Macias, A Morell, J Comas, ... Nephrology Dialysis Transplantation 38 (Supplement_1), gfad063c_4640, 2023 | | 2023 |
| POS-382 DEEP LEARNING-BASED PREDICTION FOR MORTALITY IN PATIENTS WITH CHRONIC KIDNEY DISEASE: A NEW MODEL DEVELOPED WITH DATA FROM 10.000 PATIENTS OVER THE LAST 11 YEARS O Gallés, N MONILL-RAYA, E Macias, A Morell, J Serrano, D Rexach, ... Kidney International Reports 7 (2), S172, 2022 | | 2022 |
| Multiple imputation using the average code from autoencoders E Macias, J Serrano, JL Vicario, A Morell Computer Methods and Programs in Biomedicine Update 2, 100053, 2022 | | 2022 |
| MO766 EARLY ARTERIOVENOUS FISTULA FAILURE PREDICTION WITH ARTIFICIAL INTELLIGENCE: A NEW APPROACH WITH CHALLENGING RESULTS J Ibeas, N Monill-Raya, E Macias, C Rubiella, J Vallespin, J Merino, ... Nephrology Dialysis Transplantation 36 (Supplement_1), gfab103. 004, 2021 | | 2021 |
| SO019 A PREDICTIVE MODEL OF MORTALITY IN ACUTE RENAL FAILURE IN THE CRITICAL PATIENT: USEFULNESS OF ARTIFICIAL INTELLIGENCE J Ibeas, E Lleal, E Macias, C Rubiella, A Morell, J Serrano, J Vicario Nephrology Dialysis Transplantation 35 (Supplement_3), gfaa139. SO019, 2020 | | 2020 |
| Transfer learning and data augmentation for mortality predictive models in kidney disease E Macias, J Ibeas, J Serrano, JL Vicario, A Morell | | |
Javier SerranoUniversitat Autònoma de BarcelonaVerified email at uab.cat
