Difference between revisions of "Publicaciones en Revista"
From Klinilycs
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| IEEE Signal Process. Mag (Q1), vol. 36, no 3, pp. 16-43 | | IEEE Signal Process. Mag (Q1), vol. 36, no 3, pp. 16-43 | ||
| May. 2019 | | May. 2019 | ||
| + | |- | ||
| + | | Machine Learning Techniques to Identify Antimicrobial Resistance in the Intensive Care Unit | ||
| + | | S. Martínez-Agüero, I. Mora-Jiménez, J. Lérida-García, J. Álvarez-Rodríguez, C. Soguero-Ruiz | ||
| + | | Entropy (Q2), vol. 21, no. 6, pp. 603- 24 páginas | ||
| + | | Jun. 2019 | ||
|- | |- | ||
| [https://tsc.urjc.es/~amarques/papers/srficcam_spl18.pdf Sampling and Reconstruction of Diffused Sparse Graph Signals from Successive Local Aggregations] | | [https://tsc.urjc.es/~amarques/papers/srficcam_spl18.pdf Sampling and Reconstruction of Diffused Sparse Graph Signals from Successive Local Aggregations] | ||
| Line 125: | Line 130: | ||
| IEEE Signal Process. Letters (Q2), vol. 26, no. 8, pp 1142-1146 | | IEEE Signal Process. Letters (Q2), vol. 26, no. 8, pp 1142-1146 | ||
| Aug. 2019 | | Aug. 2019 | ||
| + | |- | ||
| + | | A data-driven model based on Support Vector Machine to identify chronic hypertensive and diabetic patients | ||
| + | | C. Soguero-Ruiz, P. de Miguel-Bohoyo, I. Mora-Jiménez | ||
| + | | Physiological Computing Systems. Revised and Extended Selected Papers. Lecture Notes in Computer Science 10057. (LNCS, volume 10057). Eds A. Holzinger, A. Pope, H.P. da Silva. Ed. Springer, ISBN 978-3-030-27949-3, pp. 110-129 | ||
| + | | Aug. 2019 | ||
| + | |- | ||
| + | | Identification of Clinically Relevant Features in Hypertensive Patients using Penalized Regression: A Case Study of Cardiovascular Events | ||
| + | | R. García-Carretero, O. Barquero-Pérez, I. Mora-Jiménez, C. Soguero-Ruiz, R. Goya-Esteban, J. Ramos-López | ||
| + | | Medical & Biological Engineering & Computing (Q3), vol. 57, no. 9, pp. 2011-2026 | ||
| + | | Sep. 2019 | ||
| + | |- | ||
| + | | Prevalence and clinical features of non-alcoholic steatohepatitis in a hypertensive population | ||
| + | | R. García-Carretero, O. Barquero-Pérez, I. Mora-Jiménez, C. Soguero-Ruiz, R. Goya-Esteban, C. Rodríguez-Castro, J. Ramos-López | ||
| + | | Hipertensión y Riesgo Vascular vol. 36, no. 3, pp. 130-136 | ||
| + | | Sep. 2019 | ||
|- | |- | ||
|} | |} | ||
Revision as of 11:29, 21 January 2021
Contents
Año 2021[edit]
| Título | Autor/es | Revista | Fecha Publicación |
|---|---|---|---|
| Electrocardiographic imaging including intracardiac information to achieve accurate global mapping during atrial fibrillation | M. A. Cámara Vázquez, I. Hernández Romero, M. Rodrigo, F. Alonso Atienza, Carlos Figuera Pozuelo, Eduardo Morgado Reyes, F. Atienza, M. S.Guillem, A. M.Climent, Ó. Barquero Pérez | Biomedical Signal Processing and Control, Elsevier (Q2), vol. 64, pp. 102354 | Feb. 2021 |
Año 2020[edit]
| Título | Autor/es | Revista | Fecha Publicación |
|---|---|---|---|
| Artificial Intelligence to Get Insights of Multi-drug Resistance Risk Factors during the First 48 Hours from ICU Admission | I. Mora-Jiménez , J. Tarancón-Rey , J. Álvarez-Rodríguez , C. Soguero-Ruiz | Antibiotics | ? |
| Data and Network Analytics for COVID-19 ICU Patients: A Case Study for a Spanish Hospital | S. Martínez-Agüero, A. García Marqués, I. Mora-Jiménez, J. Álvarez-Rodríguez, C. Soguero-Ruiz | IEEE Journal of Biomedical and Health Informatics | ? |
| Antimicrobial Resistance Prediction in Intensive Care Unit for Pseudomonas Aeruginosa using Temporal Data-Driven Models | À. Hernàndez-Carnerero, M. Sànchez-Marrè, I. Mora-Jiménez2, C. Soguero-Ruiz, S. Martínez-Agüero, J. Álvarez-Rodríguez | International Journal of Interactive Multimedia and Artificial Intelligence. | ? |
| Invariance Preserving Localized Activation Functions for Graph Neural Networks | L. Ruíz, F. Gama, A. García Marqués, and A. Ribeiro | IEEE Trans. Signal Process (Q1), vol. 68, pp. 127-141 | Jan. 2020 |
| R. García-Carretero, L. Vigil-Medina, O. Barquero-Pérez, I. Mora-Jiménez, C. Soguero-Ruiz, R. Goya-Esteban, J. Ramos-López | Logistic LASSO and elastic net to characterize vitamin D deficiency in a hypertensive obese population | Metabolic Syndrome and Related Disorders (Q4), vol. 18, no. 2, pp. 79-85 | Jan. 2020 |
| Rethinking Sketching as Sampling: A Graph Signal Processing Approach | F. Gama, A. García Marqués, G. Mateos, and A. Ribeiro | Signal Processing, Elsevier (Q1), vol. 169, 107404 | Jan. 2020 |
| Informative Variable Identifier: Expanding Interpretability in Feature Selection | S. Muñoz-Romero, A. Gorostiaga, C. Soguero-Ruiz, I. Mora-Jiménez, JL Rojo-Álvarez | Pattern Recognition (Q1), vol. 98, pp. 1-19 | Feb. 2020 |
| Visually guided classification trees for analyzing chronic patients | C. Soguero-Ruiz, I. Mora-Jiménez, M.A. Mohedano-Munoz, M.Rubio-Sanchez, P. de Miguel-Bohoyo, A. Sanchez | BMC Bioinformatics (Q1), vol. 21, 92 (19 páginas) | Mar. 2020 |
| Use of a K-Nearest Neighbors Model to Predict the Development of Type 2 Diabetes Within 2 Years in an Obese, Hypertensive Population | R. García-Carretero, L. Vigil-Medina, I. Mora-Jiménez, C. Soguero-Ruiz, O. Barquero-Pérez, J. Ramos-López | Medical & Biological Engineering & Computing (Q2), vol. 58, no. 5, pp. 991-1002 | May. 2020 |
| Estimating Network Processes via Blind Identification of Multiple Graph Filters | Y. Zhu, F. J. Iglesias García, A. García Marqués, and S. Segarra | IEEE Trans. Signal Process (Q1), vol. 68, pp. 3049-3063 | May. 2020 |
| Data-Driven Visual Characterization of Patient Health-Status using Electronic Health Records and Self-Organizing Maps | D. Chushig-Muzo, C. Soguero-Ruiz, A. Engelbrecht, P. de Miguel-Bohoyo, I. Mora-Jiménez | IEEE Access (Q1), vol. 8, pp. 137019-137031 | Jul. 2020 |
| Quantitative Cluster Headache Analysis for Neurological Diagnosis Support using Statistical Classification | M El-Yaagoubi, I Mora-Jiménez, Y Jabrane, S Muñoz-Romero, JL Rojo-Álvarez, JA Pareja-Grande | Information, vol. 11, no. 393, pp. 1-13 | Aug. 2020 |
| Autonomic Nervous System and Recall Modeling in Audiovisual Advertising Emotion Mediated using Partial Least Squares Path modeling | O. Barquero Pérez, M. Cámara Vázquez, A. Vadillo Valderrama, and R. Goya Esteban | Frontiers in Psychology (Q1), vol. 11, pp. 576771 | Oct. 2020 |
| Tensor Graph Convolutional Networks: Multi relational and Robust Learning | V. N. Ioannidis, A. García Marqués, and G. B. Giannakis | IEEE Trans. Signal Process (Q1) | Oct. 2020 |
| Graph Signal Processing: Foundations and Emerging Directions (Editorial) | A. García Marqués, N. Kiyavash, J. M. F. Moura, D. Van De Ville, and R. Willett | IEEE Signal Process. Mag (Q1), vol. 37 | Nov. 2020 |
| Signal Processing over Directed Graphs | A. García Marqués, S. Segarra, and G. Mateos | IEEE Signal Process. Mag (Q1), vol. 37 | Nov. 2020 |
Año 2019[edit]
| Título | Autor/es | Revista | Fecha Publicación |
|---|---|---|---|
| Convolutional Neural Networks Architectures for Signals Supported on Graphs | F. Gama, A. García Marqués, G. Leus, and A. Ribeiro | IEEE Trans. Signal Process (Q1), vol. 67, no. 4, pp. 1034-1049 | Feb. 2019 |
| Connecting the Dots: Identifying Network Structure via Graph Signal Processing | G. Mateos, S. Segarra, A. García Marqués, and A. Ribeiro | IEEE Signal Process. Mag (Q1), vol. 36, no 3, pp. 16-43 | May. 2019 |
| Machine Learning Techniques to Identify Antimicrobial Resistance in the Intensive Care Unit | S. Martínez-Agüero, I. Mora-Jiménez, J. Lérida-García, J. Álvarez-Rodríguez, C. Soguero-Ruiz | Entropy (Q2), vol. 21, no. 6, pp. 603- 24 páginas | Jun. 2019 |
| Sampling and Reconstruction of Diffused Sparse Graph Signals from Successive Local Aggregations | S. Rey Escudero, F. J. Iglesias García, C. Cabrera Guerrero, and A. García Marqués | IEEE Signal Process. Letters (Q2), vol. 26, no. 8, pp 1142-1146 | Aug. 2019 |
| A data-driven model based on Support Vector Machine to identify chronic hypertensive and diabetic patients | C. Soguero-Ruiz, P. de Miguel-Bohoyo, I. Mora-Jiménez | Physiological Computing Systems. Revised and Extended Selected Papers. Lecture Notes in Computer Science 10057. (LNCS, volume 10057). Eds A. Holzinger, A. Pope, H.P. da Silva. Ed. Springer, ISBN 978-3-030-27949-3, pp. 110-129 | Aug. 2019 |
| Identification of Clinically Relevant Features in Hypertensive Patients using Penalized Regression: A Case Study of Cardiovascular Events | R. García-Carretero, O. Barquero-Pérez, I. Mora-Jiménez, C. Soguero-Ruiz, R. Goya-Esteban, J. Ramos-López | Medical & Biological Engineering & Computing (Q3), vol. 57, no. 9, pp. 2011-2026 | Sep. 2019 |
| Prevalence and clinical features of non-alcoholic steatohepatitis in a hypertensive population | R. García-Carretero, O. Barquero-Pérez, I. Mora-Jiménez, C. Soguero-Ruiz, R. Goya-Esteban, C. Rodríguez-Castro, J. Ramos-López | Hipertensión y Riesgo Vascular vol. 36, no. 3, pp. 130-136 | Sep. 2019 |
Año 2018[edit]
| Título | Autor/es | Revista | Fecha Publicación |
|---|---|---|---|
| Arrhythmia Mechanism and Scaling Effect on the Spectral Properties of Electroanatomical Maps with Manifold Harmonics | M. Sanromán Junquera, I. Mora Jiménez, A. García Alberola, A.J. Caamaño Fernández, B. Trénor Gomis, J. L. Rojo Álvarez | IEEE Transactions on Biomedical Engineering (Q1), vol. 65, no. 4, pp. 723
732 |
Apr. 2018 |
| Time series cluster kernel for learning similarities between multivariate time series with missing data | K. Ø. Mikalsen, F. Bianchi, C. Soguero Ruíz, R. Jenssen | Pattern Recognition (Q1), vol. 76, pp. 569 581 | Apr. 2018 |
| Cardiovascular risk assessment in prediabetic patients in a hypertensive population: The role of cystatin C | R. García Carretero, L. Vigil Medina, I. Mora Jiménez, C. Soguero Ruíz, R. Goya Esteban, J Ramos López, O. Barquero Pérez | Diabetes Metab Syndr, vol. 12, no.5, pp. 625 629 | Apr. 2018 |
| Scaled Radial Axes for Interactive Visual Feature Selection: A Case Study for Analyzing Chronic Conditions | A. Sánchez, C. Soguero Ruíz, I. Mora Jiménez, F. J. Rivas Flores, D. J. Lehmann, M. Rubio Sánchez | Expert Systems with Applications (Q1), vol. 100, pp. 182 196 | Jun. 2018 |
| Convex Programming and Bootstrap Sensitivity for Optimized Electricity Bill in Healthcare Buildings under a Time of use Pricing Scheme | R. Gordillo Orquera, S. Muñoz Romero, D. Arcos Avilés, R. Chillón, L. M. López Ramos, A. García Marqués, J. L. Rojo Álvarez | Energies 2018, 11(6), 1454. | Jun. 2018 |
| Riemann Langevin Particle Filtering in Track Before Detect | F. J. Iglesias García, P. K. Mandal, M. Bocquel, and A. García Marqués | IEEE Signal Process. Letters (Q2), vol. 25, no. 7, pp. 1039 1043 | Jul. 2018 |
| Classifying Cardiac Arrhythmic Episodes via Data Compression | J.M. Lillo Castellano, J.L. Rojo Álvarez, F. Chavarría Asso, A. García García, M. Marín Méndez, A. García Alberola, I. Mora Jiménez | Neurocomputing (Q1), vol. 307, pp.1 13 | Sep. 2018 |
| Rating Prediction via Graph Signal Processing | W. Huang, A. García Marqués, and A. Ribeiro | IEEE Trans. Signal Process (Q1), vol. 66, no. 19, pp. 5066 5081 | Oct. 2018 |
Año 2017[edit]
| Título | Autor/es | Revista | Fecha Publicación |
|---|---|---|---|
| Analysis of free text in electronic health records for identification of cancer patient trajectories | K. Jensen, C. Soguero Ruíz, K.O Mikalsen, R O Lindsetmo, I. Kouskoumvekaki, M. Girolami, S.O Skrovseth, K. M. Augestad | Scientific Reports (Q1), vol. 7, no. 46226 | Apr. 2017 |
| Optimal Graph Filter Design and Applications to Distributed Linear Network Operators | S. Segarra, A. García Marqués, and A. Ribeiro | IEEE Trans. Signal Process. (Q1), vol. 65, no. 15, pp. 4117 4131 | Aug. 2017 |
| Network Topology Inference from Spectral Templates | S. Segarra, A. García Marqués, G. Mateos, and A. Ribeiro | IEEE Trans. Signal Inf. Process. Netw., vol. 3, no. 3, pp. 467 483 | Sept. 2017 |
| Stationary Graph Processes and Spectral Estimation | A. García Marqués, S. Segarra, G. Leus, and A. Ribeiro, | IEEE Trans. Signal Process. (Q1), vol. 65, no. 22, pp. 5911 5926 | Nov. 2017 |
| Using anchors from free text in electronic health records to diagnose postoperative delirium | K. Ø. Mikalsen, C. Soguero Ruíz, K. Jensen, K. Hindberg, M. Gran, A. Revhaug, R O Lindsetmo, S.O Skrøvseth, F. Godtliebsen, R. Jenssen | Computer Methods and Programs in Biomedicine (Q2), vol. 152,
pp.105 114 |
Dec. 2017 |
| Cystatin C as a predictor of cardiovascular outcomes in a hypertensive population | R. García Carretero, L. Vigil Medina, O. Barquero Pérez, R. Goya Esteban, I. Mora Jiménez, C. Soguero Ruíz, J. Ramos López | Journal of Human Hypertension 31 (Q3), vol. 12, pp. 801 807 | Dec. 2017 |
