Alberto Fernández Hilario

Highly Cited Researcher 2017 - CV -


Researcher Profile

Total From 2017:
Citas Total: 15506 From 2017: 10535
Índice H Total: 43 From 2017: 38
Índice i10 Total: 75 From 2017: 61

Papers (158)

Title Authors Year
Learning interpretable multi-class models by means of hierarchical decomposition: Threshold Control for Nested Dichotomies JA Fdez-Sánchez, JD Pascual-Triana, A Fernández, F Herrera. 2021
SOUL: Scala Oversampling and Undersampling Library for imbalance classification N Rodríguez, D López, A Fernández, S García, F Herrera. 2021
IFC-BD: An Interpretable Fuzzy Classifier for Boosting Explainable Artificial Intelligence in Big Data F Aghaeipoor, MM Javidi, A Fernandez. 2021
IEEE Computational Intelligence Society J Cózar, A Fernández, F Herrera, JA Gámez. 2021
FDR2-BD: A Fast Data Reduction Recommendation Tool for Tabular Big Data Classification Problems MJ Basgall, M Naiouf, A Fernández. 2021
Revisiting Data Complexity Metrics Based on Morphology for Overlap and Imbalance: Snapshot, New Overlap Number of Balls Metrics and Singular Problems Prospect JD Pascual-Triana, D Charte, MA Arroyo, A Fernández, F Herrera. 2020
Towards Smart Data Technologies for Big Data Analytics MJ Basgall, M Naiouf, F Herrera, A Fernández. 2020
HFER: Promoting Explainability in Fuzzy Systems via Hierarchical Fuzzy Exception Rules JR Trillo, A Fernandez, F Herrera. 2020
Chi-BD-DRF: Design of Scalable Fuzzy Classifiers for Big Data via A Dynamic Rule Filtering Approach F Aghaeipoor, MM Javidi, I Triguero, A Fernández. 2020
Discussion on Vuttipittayamongkol, P. and Elyan, E., Improved Overlap-Based Undersampling for Imbalanced Dataset Classification with Application to Epilepsy and Parkinson’s Disease A Fernández. 2020
Applying Feature Selection to Improve Predictive Performance and Explainability in Lung Cancer Detection with Soft Computing N Potie, S Giannoukakos, M Hackenberg, A Fernandez. 2020
Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to? A Fernandez, F Herrera, O Cordon, MJ del Jesus, F Marcelloni. 2019
A multi-objective evolutionary fuzzy system to obtain a broad and accurate set of solutions in intrusion detection systems S Elhag, A Fernández, A Altalhi, S Alshomrani, F Herrera. 2019
An Analysis of Local and Global Solutions to Address Big Data Imbalanced Classification: A Case Study with SMOTE Preprocessing MJ Basgall, W Hasperué, M Naiouf, A Fernández, F Herrera. 2019
Guest Editorial: Computational Intelligence for Big Data Analytics A Fernandez, I Triguero, M Galar, F Herrera. 2019
Allergy to vegetables belonging to the Solanaceae family M Tomás-Pérez, I Hernández-Martín, API Fernández, MJ Pagola, .... 2019
Evolutionary fuzzy systems: a case study for intrusion detection systems S Elhag, A Fernández, S Alshomrani, F Herrera. 2019
On the need of interpretability for biomedical applications: Using fuzzy models for lung cancer prediction with liquid biopsy N Potie, S Giannoukakos, M Hackenberg, A Fernandez. 2019
XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018) JDELSER FRANCISCO HERRERA, SERGIO DAMAS, ROSANA MONTES, SERGIO ALONSO .... 2018
SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary A Fernandez, S Garcia, F Herrera, NV Chawla. 2018
Big data: Tutorial and guidelines on information and process fusion for analytics algorithms with MapReduce S Ramírez-Gallego, A Fernández, S García, M Chen, F Herrera. 2018
Dynamic affinity-based classification of multi-class imbalanced data with one-versus-one decomposition: a fuzzy rough set approach S Vluymans, A Fernández, Y Saeys, C Cornelis, F Herrera. 2018
Imbalance: oversampling algorithms for imbalanced classification in R I Cordón, S García, A Fernández, F Herrera. 2018
A Metahierarchical Rule Decision System to Design Robust Fuzzy Classifiers Based on Data Complexity J Cózar, A Fernández, F Herrera, JA Gámez. 2018
Learning from Imbalanced Data Sets A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. 2018
Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers D Galpert, A Fernández, F Herrera, A Antunes, R Molina-Ruiz, .... 2018
SMOTE-BD: An Exact and Scalable Oversampling Method for Imbalanced Classification in Big Data MJ Basgall, W Hasperué, M Naiouf, A Fernández, F Herrera. 2018
Cost-sensitive learning A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. 2018
Imbalanced Classification for Big Data A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. 2018
Learning from Imbalanced Data Streams A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. 2018
Data Intrinsic Characteristics A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. 2018
Performance measures A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. 2018
Ensemble learning A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. 2018
Algorithm-Level Approaches A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. 2018
Data Level Preprocessing Methods A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. 2018
Imbalanced Classification with Multiple Classes A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. 2018
Introduction to KDD and Data Science A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. 2018
Non-classical Imbalanced Classification Problems A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. 2018
Dimensionality Reduction for Imbalanced Learning A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. 2018
Foundations on Imbalanced Classification A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. 2018
Software and Libraries for Imbalanced Classification A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. 2018
NMC, Nearest Matrix Classification: A new combination model for pruning one-vs-one ensembles by transforming the aggregation problem MG Idoate, A Fernández, EB Tartas, HB Sola, F Herrera. 2018
Improving fuzzy rule based classification systems in big data via support-based filtering L Íniguez, M Galar, A Fernández. 2018
A Pareto-based ensemble with feature and instance selection for learning from multi-class imbalanced datasets A Fernández, CJ Carmona, M Jose del Jesus, F Herrera. 2017
KEEL 3.0: an open source software for multi-stage analysis in data mining I Triguero, S González, JM Moyano, S García López, J Alcalá Fernández, .... 2017
Can Bioinformatics close the gender gap in STEM skills?: Reflections from the I Bioinformatics UGR Workshop C del Val, E Ruiz, R Alcalá, A Fernández, C Cano, W Fajardo, .... 2017
An insight into imbalanced Big Data classification: outcomes and challenges A Fernández, S del Río, NV Chawla, F Herrera. 2017
Fuzzy rule based classification systems for big data with MapReduce: granularity analysis A Fernández, S del Río, A Bawakid, F Herrera. 2017
NMC: nearest matrix classification–A new combination model for pruning One-vs-One ensembles by transforming the aggregation problem M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera. 2017
Why Linguistic Fuzzy Rule Based Classification Systems perform well in Big Data Applications? A Fernández, S Alshomrani, A Altalhi, F Herrera. 2017
Chi-Spark-RS: An Spark-built evolutionary fuzzy rule selection algorithm in imbalanced classification for big data problems A Fernandez, E Almansa, F Herrera. 2017
A Review of Distributed Data Models for Learning MÁ Rodríguez, A Fernández, A Peregrín, F Herrera. 2017
Metodología para el análisis y predicción de la contaminación fecal mediante el uso de redes neuronales artificiales. Aplicación a la playa de la Arena (Muskiz) J García Alba, JF Bárcena Gómez, I Claramunt González, .... 2017
A view on fuzzy systems for big data: progress and opportunities A Fernández, CJ Carmona, MJ del Jesus, F Herrera. 2016
Comparison of KEEL versus open source Data Mining tools: Knime and Weka software I Triguero, S González, JM Moyano, S García, J Alcala-Fdez, J Luengo, .... 2016
Ordering-Based Pruning for Improving the Performance of Ensembles of Classifiers in the Framework of Imbalanced Datasets M Galar, A Fernandez, E Barrenechea, H Bustince, H Francisco. 2016
Enhancing Evolutionary Fuzzy Systems for Multi-Class Problems: Distance-based Relative Competence Weighting with Truncated Confidences (DRCW-TC) A Fernandez, M Elkano, M Galar, JA Sanz, S Alshomrani, H Bustince, .... 2016
Evolutionary Fuzzy Systems: A Case Study in Imbalanced Classification A Fernández, F Herrera. 2016
On the combination of pairwise and granularity learning for improving fuzzy rule-based classification systems: GL-FARCHD-OVO P Villar, A Fernández, F Herrera. 2016
GL-FARCHD-OVO P Villar, A Fernández, F Herrera. 2016
A first approach in evolutionary fuzzy systems based on the lateral tuning of the linguistic labels for big data classification A Fernández, S del Río, F Herrera. 2016
New Ordering-Based Pruning Metrics for Ensembles of Classifiers in Imbalanced Datasets M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera. 2016
Revisiting evolutionary fuzzy systems: Taxonomy, applications, new trends and challenges A Fernandez, V Lopez, MJ del Jesus, F Herrera. 2015
Addressing overlapping in classification with imbalanced datasets: A first multi-objective approach for feature and instance selection A Fernández, MJ del Jesus, F Herrera. 2015
HYBRID COMPUTATIONAL INTELLIGENCE A Fernández, R Alcalá, JM Benítez, F Herrera. 2015
On the combination of genetic fuzzy systems and pairwise learning for improving detection rates on intrusion detection systems S Elhag, A Fernández, A Bawakid, S Alshomrani, F Herrera. 2015
DRCW-OVO: distance-based relative competence weighting combination for one-vs-one strategy in multi-class problems M Galar, A Fernández, E Barrenechea, F Herrera. 2015
A proposal for evolutionary fuzzy systems using feature weighting: dealing with overlapping in imbalanced datasets S Alshomrani, A Bawakid, SO Shim, A Fernández, F Herrera. 2015
On the impact of Distance-based Relative Competence Weighting approach in One-vs-One classification for Evolutionary Fuzzy Systems: DRCW-FH-GBML algorithm A Fernández, M Galar, JA Sanz, H Bustince, O Cordón, F Herrera. 2015
Improving the OVO performance in fuzzy rule-based classification systems by the genetic learning of the granularity level P Villar, A Fernández, R Montes, AM Sánchez, F Herreraz. 2015
Improving Pairwise Learning Classification in Fuzzy Rule Based Classification Systems Using Dynamic Classifier Selection A Fernández, M Galar, JA Sanz, H Bustince, F Herrera. 2015
Design of an enhanced MEIGA-MetNet dust micro-sensor able to perform gas sensing in Mars atmosphere MA Rodríguez, A Fernández, F Cortés, F López. 2015
Propuesta de una asignatura de Diseño de Servidores para la especialidad de Tecnologías de Información AJ Rivera Rivas, M Espinilla, A Fernández Hilario, J Santamaría López, .... 2014
Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks A Fernández, S del Río, V López, A Bawakid, MJ del Jesus, JM Benítez, .... 2014
2. Addressing the Data Intrinsic Characteristics of Imbalanced Problems using FRBCSs and Machine Learning Techniques V López, A Fernández, MJ del Jesus, F Herrera. 2014
E-learning and educational data mining in cloud computing: an overview A Fernández, D Peralta, JM Benítez, F Herrera. 2014
On the importance of the validation technique for classification with imbalanced datasets: Addressing covariate shift when data is skewed V López, A Fernández, F Herrera. 2014
Enhancing Multiclass Classification in FARC-HD Fuzzy Classifier: On the Synergy Between-Dimensional Overlap Functions and Decomposition Strategies M Elkano, M Galar, JA Sanz, A Fernández, E Barrenechea, F Herrera, .... 2014
Empowering difficult classes with a similarity-based aggregation in multi-class classification problems M Galar, A Fernández, E Barrenechea, F Herrera. 2014
Enhancing difficult classes in one-vs-one classifier fusion strategy using restricted equivalence functions M Galar, E Barrenechea, A Fernández, F Herrera. 2014
Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches A FernáNdez, V LóPez, M Galar, MAJ Del Jesus, F Herrera. 2013
A hierarchical genetic fuzzy system based on genetic programming for addressing classification with highly imbalanced and borderline data-sets V LóPez, A FernáNdez, MAJ Del Jesus, F Herrera. 2013
An overview on the structure and applications for business intelligence and data mining in cloud computing A Fernández, S del Río, F Herrera, JM Benítez. 2013
An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics V López, A Fernández, S García, V Palade, F Herrera. 2013
EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling M Galar, A Fernández, E Barrenechea, F Herrera. 2013
IVTURS: A linguistic fuzzy rule-based classification system based on a new interval-valued fuzzy reasoning method with tuning and rule selection JA Sanz, A Fernandez, H Bustince, F Herrera. 2013
Dynamic classifier selection for one-vs-one strategy: avoiding non-competent classifiers M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera. 2013
Addressing covariate shift for genetic fuzzy systems classifiers: a case of study with FARC-HD for imbalanced datasets V López, A Fernández, F Herrera. 2013
Cost Sensitive and Preprocessing for Classification with Imbalanced Data-sets: Similar Behaviour and Potential Hybridizations. V López, A Fernández, MJ Del Jesus, F Herrera. 2012
An overview of e-learning in cloud computing A Fernandez, D Peralta, F Herrera, JM Benítez. 2012
A review on ensembles for the class imbalance problem: bagging-, boosting-, and hybrid-based approaches M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera. 2012
Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics V López, A Fernández, JG Moreno-Torres, F Herrera. 2012
Feature selection and granularity learning in genetic fuzzy rule-based classification systems for highly imbalanced data-sets P Villar, A Fernandez, RA Carrasco, F Herrera. 2012
IIVFDT: Ignorance functions based interval-valued fuzzy decision tree with genetic tuning J Sanz, H Bustince, A Fernández, F Herrera. 2012
Linguistic fuzzy rules in data mining: follow-up Mamdani fuzzy modeling principle A Fernández, F Herrera. 2012
On the usefulness of fuzzy rule based systems based on hierarchical linguistic fuzzy partitions A Fernández, V López, MJ Del Jesus, F Herrera. 2011
Addressing data complexity for imbalanced data sets: analysis of SMOTE-based oversampling and evolutionary undersampling J Luengo, A Fernández, S García, F Herrera. 2011
Using KEEL software as a educational tool: A case of study teaching data mining J Derrac, J Luengo, J Alcala-Fdez, A Fernandez, S Garcia. 2011
KEEL data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework J Alcala-Fdez, A Fernández, J Luengo, J Derrac, S García, L Sánchez, .... 2011
An overview of ensemble methods for binary classifiers in multi-class problems: Experimental study on one-vs-one and one-vs-all schemes M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera. 2011
A genetic tuning to improve the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets: Degree of ignorance and lateral position J Sanz, A Fernández, H Bustince, F Herrera. 2011
Addressing the classification with imbalanced data: open problems and new challenges on class distribution A Fernández, S García, F Herrera. 2011
Aggregation Schemes for Binarization Techniques Methods' Description M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera. 2011
A case study on medical diagnosis of cardiovascular diseases using a genetic algorithm for tuning fuzzy rule-based classification systems with interval-valued fuzzy sets J Sanz, M Pagola, H Bustince, A Brugos, A Fernández, F Herrera. 2011
Construction of interval-valued fuzzy preference relations using ignorance functions: Interval-valued non dominance criterion E Barrenechea, A Fernández, F Herrera, H Bustince. 2011
Studying the behavior of a multiobjective genetic algorithm to design fuzzy rule-based classification systems for imbalanced data-sets P Villar, A Fernández, F Herrera. 2011
On the cooperation of interval-valued fuzzy sets and genetic tuning to improve the performance of fuzzy decision trees JA Sanz, H Bustince, A Fernández, F Herrera. 2011
Aggregation schemes for binarization techniques Methods’ description M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera. 2011
On the 2-tuples based genetic tuning performance for fuzzy rule based classification systems in imbalanced data-sets A Fernández, MJ del Jesus, F Herrera. 2010
Multi-class imbalanced data-sets with linguistic fuzzy rule based classification systems based on pairwise learning A Fernández, MJ Del Jesus, F Herrera. 2010
Analysis of an evolutionary RBFN design algorithm, CO2RBFN, for imbalanced data sets MD Pérez-Godoy, A Fernández, AJ Rivera, MJ del Jesus. 2010
Analysing the hierarchical fuzzy rule based classification systems with genetic rule selection A Fernández, MJ del Jesús, F Herrera. 2010
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power S García, A Fernández, J Luengo, F Herrera. 2010
Genetics-based machine learning for rule induction: state of the art, taxonomy, and comparative study A Fernández, S García, J Luengo, E Bernadó-Mansilla, F Herrera. 2010
Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuning JA Sanz, A Fernández, H Bustince, F Herrera. 2010
Solving multi-class problems with linguistic fuzzy rule based classification systems based on pairwise learning and preference relations A Fernández, M Calderón, E Barrenechea, H Bustince, F Herrera. 2010
A genetic algorithm for tuning fuzzy rule-based classification systems with interval-valued fuzzy sets J Sanz, A Fernández, H Bustince, F Herrera. 2010
A genetic algorithm for feature selection and granularity learning in fuzzy rule-based classification systems for highly imbalanced data-sets P Villar, A Fernández, F Herrera. 2010
A first approach for cost-sensitive classification with linguistic genetic fuzzy systems in imbalanced data-sets V López, A Fernández, F Herrera. 2010
USING SIMILARITY MEASURES IN FUZZY RULE-BASED CLASSIFICATION SYSTEMS WITH INTERVAL-VALUED FUZZY SETS J Sanz, D Jurío, A Fernández, F Herrera, H Bustince. 2010
Sistemas de clasificación basados en reglas difusas lingüísticas aplicadas a problemas con clases no balanceadas A Fernández Hilario. 2010
Un primer estudio sobre el uso de aprendizaje sensible al coste con sistemas de clasificación basados en reglas difusas para problemas no balanceados V López, A Fernández, F Herrera. 2010
Descripción, Descubrimiento y Composición de Servicios en Entornos Multiagente Abiertos. Un Enfoque Organizacional A Fernández. 2010
Dispositivos móviles iPod touch y iPad para Aprendizaje en Educación Especial A Fernández, MJ Rodríguez. 2010
Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets A Fernández, MJ del Jesus, F Herrera. 2009
On the influence of an adaptive inference system in fuzzy rule based classification systems for imbalanced data-sets A Fernández, MJ del Jesus, F Herrera. 2009
Improving the performance of fuzzy rule based classification systems for highly imbalanced data-sets using an evolutionary adaptive inference system A Fernández, MJ del Jesus, F Herrera. 2009
A Preliminar Analysis of CO2RBFN in Imbalanced Problems MD Pérez-Godoy, AJ Rivera, A Fernández, MJ del Jesús, F Herrera. 2009
A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability S García, A Fernández, J Luengo, F Herrera. 2009
Addressing data-complexity for imbalanced data-sets: A preliminary study on the use of preprocessing for c4. 5 J Luengo, A Fernández, S García, F Herrera. 2009
Implementation and integration of algorithms into the KEEL data-mining software tool A Fernández, J Luengo, J Derrac, J Alcalá-Fdez, F Herrera. 2009
Enhancing the effectiveness and interpretability of decision tree and rule induction classifiers with evolutionary training set selection over imbalanced problems S García, A Fernández, F Herrera. 2009
Enhancing fuzzy rule based systems in multi-classification using pairwise coupling with preference relations A Fernández, M Calderón, E Barrenechea, H Bustince, F Herrera. 2009
A genetic learning of the fuzzy rule-based classification system granularity for highly imbalanced data-sets P Villar, A Fernández, F Herrera. 2009
A First Study on the Use of Interval-Valued Fuzzy Sets with Genetic Tuning for Classification with Imbalanced Data-Sets J Sanz, A Fernández, H Bustince, F Herrera. 2009
Genetic Cooperative-Competitive Fuzzy Rule Based Learning Method using Genetic Programming for Highly Imbalanced Data-Sets A Fernández, FJ Berlanga, MJ del Jesus, F Herrera. 2009
Un algoritmo genético para selección de características en sistemas de clasificación basados en reglas difusas para conjuntos de datos altamente no balanceados P Villar, A Fernández, A Sánchez, F Herrera. 2009
On the site specific amplification functions for Center and Eastern United States J Garcia, A Fernandez, J Wang. 2009
A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets A Fernández, S García, MJ del Jesus, F Herrera. 2008
KEEL: A data mining software tool integrating genetic fuzzy systems J Alcalá-Fdez, S García, FJ Berlanga, A Fernández, L Sánchez, .... 2008
A short study on the use of genetic 2-tuples tuning for fuzzy rule based classification systems in imbalanced data-sets A Fernández, MJ del Jesus, F Herrera. 2008
An analysis of the rule weights and fuzzy reasoning methods for linguistic rule based classification systems applied to problems with highly imbalanced data sets A Fernández, S García, F Herrera, MJ del Jesús. 2007
A study on the use of the fuzzy reasoning method based on the winning rule vs. voting procedure for classification with imbalanced data sets A Fernández, S García, MJ Del Jesús, F Herrera. 2007
Fuzzy Machine Learning-An Analysis of the Rule Weights and Fuzzy Reasoning Methods for Linguistic Rule Based Classification Systems Applied to Problems with Highly Imbalanced … A Fernandez, S Garcia, F Herrera, MJ Jesus. 2007
Statistical comparisons by means of non-parametric tests: a case study on genetic based machine learning S García, AD Benítez, F Herrera, A Fernández. 2007
A proposal of evolutionary prototype selection for class imbalance problems S García, JR Cano, A Fernández, F Herrera. 2006
A First Study on the Use of Fuzzy Rule Based Classification Systems for Problems with Imbalanced Data Sets MJ del Jesus, A Fernández, S Garcıa, F Herrera. 2006
Wireless Network Structure-v1. 3 S Mudd, J Garcia, A Fernandez. 2002
Evaluation for prolificacy in a Large White scheme with hiperprolific animals A Fernández, MC Rodríguez, A Fuentetaja. 1999
[Evaluation for prolificacy in a Large White scheme with hiperprolific animals].[Spanish] A Fernandez, MC Rodriguez, A Fuentetaja. 1999
Melanocytic nevi in Turner syndrome F Martinon Sanchez, P Fari a, A Fernandez, MA Rodriguez, .... 1996

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