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Cristina Soguero-Ruíz
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2020 – today
- 2024
- [j33]David Chushig-Muzo
, Hugo Calero-Díaz
Interpretable Data-Driven Approach Based on Feature Selection Methods and GAN-Based Models for Cardiovascular Risk Prediction in Diabetic Patients. IEEE Access 12: 84292-84305 (2024) - [c38]Óscar Escudero-Arnanz, Rosa Sicilia, Cristina Soguero-Ruíz, Inmaculada Mora-Jiménez, Diana Lelli, Claudio Pedone, Antonio G. Marques:
Low-Rank Tensor Completion for Heart Failure Exacerbation Detection in Multivariate Time Series with Missing Data. CBMS 2024: 112-119 - [c37]Eirik Årsand, Miroslav Muzny, Tina Rishaug, Ana M. Wägner, Carmelo Betancort, Conceição Granja, Cristina Soguero-Ruíz, Gunnar Hartvigsen, Mihai Namolosanu, Mikael Rinnetmäki, André Henriksen:
Using One App Only - Collecting a Comprehensive Set of Health-Related Data for Prevention of Chronic Conditions. MIE 2024: 247-251 - [i10]Sergio Martínez-Agüero, Antonio G. Marques, Inmaculada Mora-Jiménez, Joaquín Álvarez-Rodríguez, Cristina Soguero-Ruíz:
Multimodal Interpretable Data-Driven Models for Early Prediction of Antimicrobial Multidrug Resistance Using Multivariate Time-Series. CoRR abs/2402.06295 (2024) - [i9]Vanesa Gómez-Martínez, Francisco J. Lara-Abelenda, Pablo Peiro-Corbacho, David Chushig-Muzo, Conceição Granja, Cristina Soguero-Ruíz:
LM-IGTD: a 2D image generator for low-dimensional and mixed-type tabular data to leverage the potential of convolutional neural networks. CoRR abs/2406.14566 (2024) - [i8]Óscar Escudero-Arnanz, Cristina Soguero-Ruíz, Joaquín Álvarez-Rodríguez, Antonio G. Marques:
Explainable Artificial Intelligence Techniques for Irregular Temporal Classification of Multidrug Resistance Acquisition in Intensive Care Unit Patients. CoRR abs/2407.17165 (2024) - 2023
- [j32]Álvar Hernández-Carnerero
Dimensionality reduction and ensemble of LSTMs for antimicrobial resistance prediction. Artif. Intell. Medicine 138: 102508 (2023) - [j31]Miguel A. Mohedano-Munoz
A streaming data visualization framework for supporting decision-making in the Intensive Care Unit. Expert Syst. Appl. 227: 120252 (2023) - [j30]Óscar Escudero-Arnanz
dtwParallel: A Python package to efficiently compute dynamic time warping between time series. SoftwareX 22: 101364 (2023) - [j29]Antonio J. Rodríguez-Almeida
Synthetic Patient Data Generation and Evaluation in Disease Prediction Using Small and Imbalanced Datasets. IEEE J. Biomed. Health Informatics 27(6): 2670-2680 (2023) - [c36]María Teresa Jurado-Camino
On the Use of Generative Adversarial Networks to Predict Health Status Among Chronic Patients. HEALTHINF 2023: 167-178 - [c35]Antonio J. Rodríguez-Almeida, Himar Fabelo
Novel Approach for AI-Based Risk Calculator Development Using Transfer Learning Suitable for Embedded Systems. DSD 2023: 103-110 - [e1]Mohammed Hasanuzzaman, Jyoti Prakash Singh, Gaël Dias, Cristina Soguero-Ruíz, Terje Solvoll, Phuong Dinh Ngo:
Proceedings of The First Workshop on Context-aware NLP in eHealth (WNLPe-Health 2022) co-located with The nineteenth International Conference on Natural Language Processing (ICON-2022), Delhi, India, December 15-18, 2022. CEUR Workshop Proceedings 3416, CEUR-WS.org 2023 [contents] - 2022
- [j28]David Chushig-Muzo
Learning and visualizing chronic latent representations using electronic health records. BioData Min. 15(1) (2022) - [j27]Sergio Martínez-Agüero, Cristina Soguero-Ruíz
Interpretable clinical time-series modeling with intelligent feature selection for early prediction of antimicrobial multidrug resistance. Future Gener. Comput. Syst. 133: 68-83 (2022) - [c34]Hugo Calero-Díaz
Data-driven cardiovascular risk prediction and prognosis factor identification in diabetic patients. BHI 2022: 1-4 - [c33]Jannik S. Pedersen
Domain over size: Clinical ELECTRA surpasses general BERT for bleeding site classification in the free text of electronic health records. BHI 2022: 1-4 - [c32]Carlos Arias-Alcaide, Cristina Soguero-Ruíz, Paloma Santos-Alvarez, José Felipe Varona Arche, Inmaculada Mora-Jiménez
Local Naïve Bayes for Predicting Evolution of COVID-19 Patients on Self Organizing Maps. BIBM 2022: 1443-1450 - [c31]Clara García-Vicente
Clinical Synthetic Data Generation to Predict and Identify Risk Factors for Cardiovascular Diseases. Poly/DMAH@VLDB 2022: 75-91 - [c30]Hugo Calero-Díaz
Characterizing Cardiovascular Risk Through Unsupervised and Interpretable Techniques. IDEAL 2022: 22-30 - 2021
- [j26]Margarita Rodríguez-Ibáñez
Sentiment Analysis of Political Tweets From the 2019 Spanish Elections. IEEE Access 9: 101847-101862 (2021) - [j25]David Chushig-Muzo
Interpreting clinical latent representations using autoencoders and probabilistic models. Artif. Intell. Medicine 122: 102211 (2021) - [j24]Álvar Hernández-Carnerero, Miquel Sànchez-Marrè, Inmaculada Mora-Jiménez, Cristina Soguero-Ruíz, Sergio Martínez-Agüero, Joaquín Álvarez-Rodríguez:
Antimicrobial Resistance Prediction in Intensive Care Unit for Pseudomonas Aeruginosa using Temporal Data-Driven Models. Int. J. Interact. Multim. Artif. Intell. 6(5): 119-133 (2021) - [j23]Karl Øyvind Mikalsen, Cristina Soguero-Ruíz, Filippo Maria Bianchi, Arthur Revhaug, Robert Jenssen:
Time series cluster kernels to exploit informative missingness and incomplete label information. Pattern Recognit. 115: 107896 (2021) - [j22]Sergio Martínez-Agüero
Data and Network Analytics for COVID-19 ICU Patients: A Case Study for a Spanish Hospital. IEEE J. Biomed. Health Informatics 25(12): 4340-4353 (2021) - [c29]Weam Moumouh-Ait Layachi, María Sevilla-García, Adrián García-Romero, Cristina Soguero-Ruíz, Inmaculada Mora-Jiménez
On the Statistical Differences in the Pharmacological Treatment of COVID-19 Patients. BHI 2021: 1-5 - [c28]Carlos Arias-Alcaide, Cristina Soguero-Ruíz, Paloma Santos-Alvarez, Adrián García-Romero, Inmaculada Mora-Jiménez
Mapping Health Trajectories on Self Organizing Maps using COVID-19 Patient's Blood Tests. BIBM 2021: 1251-1256 - [c27]Lidia Pascual-Sánchez
Predicting Multidrug Resistance Using Temporal Clinical Data and Machine Learning Methods. BIBM 2021: 2826-2833 - [i7]Óscar Escudero-Arnanz, Joaquín Álvarez-Rodríguez, Karl Øyvind Mikalsen, Robert Jenssen, Cristina Soguero-Ruíz:
On the Use of Time Series Kernel and Dimensionality Reduction to Identify the Acquisition of Antimicrobial Multidrug Resistance in the Intensive Care Unit. CoRR abs/2107.10398 (2021) - 2020
- [j21]Margarita Rodríguez-Ibáñez
On the Statistical and Temporal Dynamics of Sentiment Analysis. IEEE Access 8: 87994-88013 (2020) - [j20]David Chushig-Muzo
Data-Driven Visual Characterization of Patient Health-Status Using Electronic Health Records and Self-Organizing Maps. IEEE Access 8: 137019-137031 (2020) - [j19]Cristina Soguero-Ruíz, Inmaculada Mora-Jiménez
Visually guided classification trees for analyzing chronic patients. BMC Bioinform. 21-S(2): 92 (2020) - [j18]Rafael García-Carretero
Use of a K-nearest neighbors model to predict the development of type 2 diabetes within 2 years in an obese, hypertensive population. Medical Biol. Eng. Comput. 58(5): 991-1002 (2020) - [j17]Sergio Muñoz-Romero
Informative variable identifier: Expanding interpretability in feature selection. Pattern Recognit. 98 (2020) - [c26]Cristina Soguero-Ruíz, Natalia Alonso-Arteaga, Sergio Muñoz-Romero
Finding Associations among Chronic Conditions by Bootstrap and Multiple Correspondence Analysis. BIBM 2020: 2066-2073 - [c25]Óscar Escudero-Arnanz, Inmaculada Mora-Jiménez, Sergio Martínez-Agüero, Joaquín Álvarez-Rodríguez, Cristina Soguero-Ruíz:
Temporal Feature Selection for Characterizing Antimicrobial Multidrug Resistance in the Intensive Care Unit. AAI4H@ECAI 2020: 54-59 - [c24]Álvar Hernández-Carnerero, Miquel Sànchez-Marrè, Inmaculada Mora-Jiménez, Cristina Soguero-Ruíz, Sergio Martínez-Agüero, Joaquín Álvarez-Rodríguez:
Modelling Temporal Relationships in Pseudomonas Aeruginosa Antimicrobial Resistance Prediction in Intensive Care Unit. AAI4H@ECAI 2020: 60-67 - [c23]Sergio Martínez-Agüero, Inmaculada Mora-Jiménez, Joaquín Álvarez-Rodríguez, Antonio Garcia Marques, Cristina Soguero-Ruíz:
Aplying LSTM Networks to Predict Multi-drug Resistance Using Binary Multivariate Clinical Sequences. STAIRS@ECAI 2020 - [i6]Karl Øyvind Mikalsen, Cristina Soguero-Ruíz, Robert Jenssen:
A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs. CoRR abs/2002.12359 (2020)
2010 – 2019
- 2019
- [j16]Margarita Rodríguez-Ibáñez
Towards Organization Management Using Exploratory Screening and Big Data Tests: A Case Study of the Spanish Red Cross. IEEE Access 7: 80661-80674 (2019) - [j15]Primoz Kocbek
Maximizing Interpretability and Cost-Effectiveness of Surgical Site Infection (SSI) Predictive Models Using Feature-Specific Regularized Logistic Regression on Preoperative Temporal Data. Comput. Math. Methods Medicine 2019: 2059851:1-2059851:13 (2019) - [j14]Lydia González-Serrano
Entropic Statistical Description of Big Data Quality in Hotel Customer Relationship Management. Entropy 21(4): 419 (2019) - [j13]Sergio Martínez-Agüero
Machine Learning Techniques to Identify Antimicrobial Resistance in the Intensive Care Unit. Entropy 21(6): 603 (2019) - [j12]Rafael García-Carretero
Identification of clinically relevant features in hypertensive patients using penalized regression: a case study of cardiovascular events. Medical Biol. Eng. Comput. 57(9): 2011-2026 (2019) - [j11]Karl Øyvind Mikalsen, Cristina Soguero-Ruíz
Noisy multi-label semi-supervised dimensionality reduction. Pattern Recognit. 90: 257-270 (2019) - [i5]Karl Øyvind Mikalsen, Cristina Soguero-Ruíz, Filippo Maria Bianchi, Robert Jenssen:
Noisy multi-label semi-supervised dimensionality reduction. CoRR abs/1902.07517 (2019) - [i4]Karl Øyvind Mikalsen, Cristina Soguero-Ruíz, Filippo Maria Bianchi, Arthur Revhaug, Robert Jenssen:
Time series cluster kernels to exploit informative missingness and incomplete label information. CoRR abs/1907.05251 (2019) - 2018
- [j10]Juan Ramón Feijoo-Martínez
Event Analysis on Power Communication Networks With Big Data for Maintenance Forms. IEEE Access 6: 72263-72274 (2018) - [j9]Alberto Sánchez
Scaled radial axes for interactive visual feature selection: A case study for analyzing chronic conditions. Expert Syst. Appl. 100: 182-196 (2018) - [j8]Karl Øyvind Mikalsen, Filippo Maria Bianchi, Cristina Soguero-Ruíz
Time series cluster kernel for learning similarities between multivariate time series with missing data. Pattern Recognit. 76: 569-581 (2018) - [c22]Andreas Storvik Strauman, Filippo Maria Bianchi, Karl Øyvind Mikalsen, Michael Kampffmeyer, Cristina Soguero-Ruíz
Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks. BHI 2018: 307-310 - [c21]Mads A. Hansen, Karl Øyvind Mikalsen, Michael Kampffmeyer, Cristina Soguero-Ruíz
Towards deep anchor learning. BHI 2018: 315-318 - [c20]Karl Øyvind Mikalsen, Cristina Soguero-Ruíz
Using multi-anchors to identify patients suffering from multimorbidities. BIBM 2018: 1514-1521 - [c19]Cristina Soguero-Ruíz
On the Use of Decision Trees Based on Diagnosis and Drug Codes for Analyzing Chronic Patients. IWBBIO (2) 2018: 135-148 - [c18]Cristina Soguero-Ruíz
A Data-Driven Model Based on Support Vector Machine to Identify Chronic Hypertensive and Diabetic Patients. PhyCS (Selected Papers) 2018: 110-129 - [i3]Karl Øyvind Mikalsen, Cristina Soguero-Ruíz, Filippo Maria Bianchi, Arthur Revhaug, Robert Jenssen:
An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples. CoRR abs/1803.07879 (2018) - 2017
- [j7]Karl Øyvind Mikalsen, Cristina Soguero-Ruíz
Using anchors from free text in electronic health records to diagnose postoperative delirium. Comput. Methods Programs Biomed. 152: 105-114 (2017) - [c17]Rafael García-Carretero
L1 Penalized Cox Regression to Characterize Cardiovascular Events in Hypertensive Patients. CinC 2017 - [c16]Antonio G. Marques
Modeling Cardiovascular Condition Evolution in Hypertensive Population Using Graph Signal Processing. CinC 2017 - [c15]Karl Øyvind Mikalsen, Filippo Maria Bianchi, Cristina Soguero-Ruíz
The time series cluster kernel. MLSP 2017: 1-6 - [c14]Javier Fernández-Sánchez, Cristina Soguero-Ruíz, Pablo de Miguel-Bohoyo
Clinical Risk Groups Analysis for Chronic Hypertensive Patients in Terms of ICD9-CM Diagnosis Codes. PhyCS 2017: 13-22 - [i2]Karl Øyvind Mikalsen, Filippo Maria Bianchi, Cristina Soguero-Ruíz, Robert Jenssen:
Time Series Cluster Kernel for Learning Similarities between Multivariate Time Series with Missing Data. CoRR abs/1704.00794 (2017) - [i1]Andreas Storvik Strauman, Filippo Maria Bianchi, Karl Øyvind Mikalsen, Michael Kampffmeyer, Cristina Soguero-Ruíz, Robert Jenssen:
Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks. CoRR abs/1711.06516 (2017) - 2016
- [j6]Cristina Soguero-Ruíz
Predicting colorectal surgical complications using heterogeneous clinical data and kernel methods. J. Biomed. Informatics 61: 87-96 (2016) - [j5]Cristina Soguero-Ruíz
Support Vector Feature Selection for Early Detection of Anastomosis Leakage From Bag-of-Words in Electronic Health Records. IEEE J. Biomed. Health Informatics 20(5): 1404-1415 (2016) - [c13]Sergio Muñoz-Romero, Margarita Sanromán-Junquera, Cristina Soguero-Ruíz, Inmaculada Mora-Jiménez, Raúl Caulier-Cisterna, Javier Moreno-Planas, Jorge García-Quintanilla, Arcadi García-Alberola, José Luis Rojo-Álvarez:
An Approach to New Methods for Digital Processing on Optical Mapping Sequences and Electrical Mapping. CinC 2016 - [c12]Cristina Soguero-Ruíz, Alicia Guerrero-Curieses, Francisco Javier Palancar, Javier Bermejo, José Carlos Antoranz, José Luis Rojo-Álvarez:
Autocorrelation Kernel Support Vector Machines for Doppler Ultrasound M-Mode Images Denoising. CinC 2016 - 2015
- [c11]Cristina Soguero-Ruíz, Fei Wang, Robert Jenssen, Knut Magne Augestad, José Luis Rojo-Álvarez, Inmaculada Mora-Jiménez, Rolv-Ole Lindsetmo, Stein Olav Skrøvseth:
Data-driven Temporal Prediction of Surgical Site Infection. AMIA 2015 - [c10]Cristina Soguero-Ruíz
Web Application for Data Exchange and Follow-up in Heart Rate Turbulence. CinC 2015: 193-196 - [c9]Cristina Soguero-Ruíz
Kernel covariance series smoothing. MLSP 2015: 1-6 - 2014
- [j4]Cristina Soguero-Ruíz
Statistical nonlinear analysis for reliable promotion decision-making. Digit. Signal Process. 33: 156-168 (2014) - [c8]Cristina Soguero-Ruíz
Bootstrap resampling feature selection and Support Vector Machine for early detection of Anastomosis Leakage. BHI 2014: 577-580 - [c7]Alfonso Sánchez-Caro, Cristina Soguero-Ruíz, Inmaculada Mora-Jiménez, Luis Lechuga-Suárez, Javier Ramos-López, Arcadio García-Alberola, Pablo Serrano-Balazote, José Luis Rojo-Álvarez:
Towards Semantic Interoperability for Cardiovascular Risk Stratification into the Electronic Health Records Using Archetypes and SNOMED-CT. CinC 2014: 497-500 - 2013
- [j3]Cristina Soguero-Ruíz
Ontology for Heart Rate Turbulence Domain From The Conceptual Model of SNOMED-CT. IEEE Trans. Biomed. Eng. 60(7): 1825-1833 (2013) - [c6]Óscar Barquero-Pérez, Teresa Quintanilla, José García-Muñoz, Cristina Soguero-Ruíz, Mark Richard Wilby, Manuel de la Rosa, Miguel Cabañas, Iván González, Roberto Bravo, Arcadi García-Alberola, José Luis Rojo-Álvarez:
eLab: A Web-based Platform to Perform HRV Analysis and Store Cardiac Signals. CinC 2013: 21-24 - [c5]María González-González, Óscar Barquero-Pérez, Cristina Soguero-Ruíz, Juan José Sánchez-Muñoz, José Luis Rojo-Álvarez, Arcadi García-Alberola:
Nonlinear Characteristics of Ventricular FibrillationDepend on Myocardial Infarction Locations. CinC 2013: 619-622 - [c4]Francisco Javier Pulido-Hidalgo, Óscar Barquero-Pérez, Cristina Soguero-Ruíz, José Luis Rojo-Álvarez, Juan José Sánchez-Muñoz, Arcadi García-Alberola:
Spectral and Nonlinear Analysis in Surgical Ventricular Fibrillation. CinC 2013: 1123-1126 - [c3]Vanessa Frías-Martínez, Cristina Soguero-Ruíz
Forecasting socioeconomic trends with cell phone records. ACM DEV (3) 2013: 15:1-15:10 - 2012
- [j2]Cristina Soguero-Ruíz
On the differential benchmarking of promotional efficiency with machine learning modeling (I): Principles and statistical comparison. Expert Syst. Appl. 39(17): 12772-12783 (2012) - [j1]Cristina Soguero-Ruíz
On the differential benchmarking of promotional efficiency with machine learning modelling (II): Practical applications. Expert Syst. Appl. 39(17): 12784-12798 (2012) - [c2]Cristina Soguero-Ruíz, Francisco Javier Gimeno-Blanes, Inmaculada Mora-Jiménez, María Pilar Martínez-Ruiz, José Luis Rojo-Álvarez:
Deal Effect Curve and Promotional Models - Using Machine Learning and Bootstrap Resampling Test. ICPRAM (2) 2012: 537-540 - [c1]Vanessa Frías-Martínez, Cristina Soguero-Ruíz, Enrique Frías-Martínez:
Estimation of urban commuting patterns using cellphone network data. UrbComp@KDD 2012: 9-16
Coauthor Index
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last updated on 2024-10-17 20:23 CEST by the dblp team
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