José A. Sáez

2.7k total citations · 2 hit papers
43 papers, 2.0k citations indexed

About

José A. Sáez is a scholar working on Artificial Intelligence, Statistics and Probability and Molecular Biology. According to data from OpenAlex, José A. Sáez has authored 43 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 11 papers in Statistics and Probability and 5 papers in Molecular Biology. Recurrent topics in José A. Sáez's work include Machine Learning and Data Classification (25 papers), Imbalanced Data Classification Techniques (16 papers) and Advanced Statistical Methods and Models (9 papers). José A. Sáez is often cited by papers focused on Machine Learning and Data Classification (25 papers), Imbalanced Data Classification Techniques (16 papers) and Advanced Statistical Methods and Models (9 papers). José A. Sáez collaborates with scholars based in Spain, Poland and United Kingdom. José A. Sáez's co-authors include Francisco Herrera, Julián Luengo, Jerzy Stefanowski, Bartosz Krawczyk, Salvador García, Mikel Galar, Jose G. Moreno-Torres, Michał Woźniak, Victoria López and Emilio Corchado and has published in prestigious journals such as Expert Systems with Applications, British Journal of Pharmacology and IEEE Access.

In The Last Decade

José A. Sáez

42 papers receiving 1.9k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

SMOTE–IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering

2014 471 citations José A. Sáez, Julián Luengo et al. Information Sciences profile →
A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning

2012 327 citations Julián Luengo, José A. Sáez et al. profile →

Peers

José A. Sáez

EEE

CVPR

HIM

Yanmin Sun Canada

Chris Seiffert United States

César García‐Osorio Spain

Satchidananda Dehuri India

Nicolás García‐Pedrajas Spain

Dennis L. Wilson United States

Pedro J. García-Laencina Spain

George D. C. Cavalcanti Brazil

Hamïd Parvïn Iran

Siti Mariyam Shamsuddin Malaysia

Yanmin Sun Canada

José A. Sáez

1.7k ×1.2

473 ×1.6

EEE

299 ×1.0

CVPR

300 ×1.2

177 ×1.3

HIM

Citations per year, relative to José A. Sáez José A. Sáez (= 1×) peers Yanmin Sun

Countries citing papers authored by José A. Sáez

Since Specialization

Citations

This map shows the geographic impact of José A. Sáez's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by José A. Sáez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites José A. Sáez more than expected).

Fields of papers citing papers by José A. Sáez

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José A. Sáez. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by José A. Sáez. The network helps show where José A. Sáez may publish in the future.

Co-authorship network of co-authors of José A. Sáez

This figure shows the co-authorship network connecting the top 25 collaborators of José A. Sáez. A scholar is included among the top collaborators of José A. Sáez based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with José A. Sáez. José A. Sáez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Cadavieco, Javier Fombona, José A. Sáez, & S. Sánchez–Expósito. (2025). Artificial intelligence and robotics in education: Advances, challenges, and future perspectives. Social Sciences & Humanities Open. 11. 101533–101533. 2 indexed citations

Sáez, José A., et al.. (2024). Differentiating Pressure Ulcer Risk Levels through Interpretable Classification Models Based on Readily Measurable Indicators. Healthcare. 12(9). 913–913. 2 indexed citations

Sáez, José A., et al.. (2024). Compact Class-Conditional Attribute Category Clustering: Amino Acid Grouping for Enhanced HIV-1 Protease Cleavage Classification. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 21(6). 2167–2178.

Sáez, José A., et al.. (2023). Tackling the problem of noisy IoT sensor data in smart agriculture: Regression noise filters for enhanced evapotranspiration prediction. Expert Systems with Applications. 237. 121608–121608. 8 indexed citations

Sáez, José A.. (2023). Noise simulation in classification with the noisemodel R package: Applications analyzing the impact of errors with chemical data. Journal of Chemometrics. 37(5). 6 indexed citations

Sáez, José A.. (2022). Noise Models in Classification: Unified Nomenclature, Extended Taxonomy and Pragmatic Categorization. Mathematics. 10(20). 3736–3736. 8 indexed citations

Romero‐Béjar, José L., et al.. (2022). Decision-Tree-Based Approach for Pressure Ulcer Risk Assessment in Immobilized Patients. International Journal of Environmental Research and Public Health. 19(18). 11161–11161. 8 indexed citations

Sáez, José A. & José L. Romero‐Béjar. (2022). On the Suitability of Bagging-Based Ensembles with Borderline Label Noise. Mathematics. 10(11). 1892–1892. 4 indexed citations

Sáez, José A., et al.. (2021). On the suitability of stacking-based ensembles in smart agriculture for evapotranspiration prediction. Applied Soft Computing. 108. 107509–107509. 17 indexed citations

10.

Sáez, José A. & Emilio Corchado. (2021). ANCES: A novel method to repair attribute noise in classification problems. Pattern Recognition. 121. 108198–108198. 17 indexed citations

11.

Sáez, José A., Julián Luengo, & Francisco Herrera. (2015). Evaluating the classifier behavior with noisy data considering performance and robustness: The Equalized Loss of Accuracy measure. Neurocomputing. 176. 26–35. 56 indexed citations

12.

Sáez, José A., Bartosz Krawczyk, & Michał Woźniak. (2015). Handling class label noise in medical pattern classification systems. Journal of Medical Informatics & Technologies. 24. 2 indexed citations

13.

Sáez, José A., Joaquín Derrac, Julián Luengo, & Francisco Herrera. (2014). Statistical computation of feature weighting schemes through data estimation for nearest neighbor classifiers. Pattern Recognition. 47(12). 3941–3948. 29 indexed citations

14.

Sáez, José A., Julián Luengo, Jerzy Stefanowski, & Francisco Herrera. (2014). SMOTE–IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering. Information Sciences. 291. 184–203. 471 indexed citations breakdown →

15.

Sáez, José A.. (2011). El fundamento ético-jurídico de la medida de seguridad de internamiento psiquiátrico. Diario La Ley. 3. 1 indexed citations

16.

Sáez, José A., Julián Luengo, & Francisco Herrera. (2010). A first study on the noise impact in classes for Fuzzy Rule Based Classification Systems. 12. 153–158. 5 indexed citations

17.

Sáez, José A., Francisco Vives, I. Domı́nguez, et al.. (1998). Electrophysiological and neurochemical study of the rat geniculo‐cortical pathway. Evidence for glutamatergic neurotransmission. European Journal of Neuroscience. 10(9). 2790–2801. 6 indexed citations

18.

Sáez, José A., et al.. (1996). Mediation by neurotensin‐receptors of effects of neurotensin on self‐stimulation of the medial prefrontal cortex. British Journal of Pharmacology. 119(2). 299–302. 2 indexed citations

19.

Ferrer, José M. Rodríguez, et al.. (1993). Neurotensin participates in self-stimulation of the medial prefrontal cortex in the rat. European Journal of Pharmacology. 231(1). 39–45. 5 indexed citations

20.

Sáez, José A., et al.. (1992). Neuromedin N decreases self-stimulation of the medial prefrontal cortex. Neuroreport. 3(11). 1027–1029. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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