Olga Valenzuela

1.8k total citations
84 papers, 1.1k citations indexed

About

Olga Valenzuela is a scholar working on Artificial Intelligence, Molecular Biology and Signal Processing. According to data from OpenAlex, Olga Valenzuela has authored 84 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Artificial Intelligence, 13 papers in Molecular Biology and 11 papers in Signal Processing. Recurrent topics in Olga Valenzuela's work include Fuzzy Logic and Control Systems (20 papers), Neural Networks and Applications (18 papers) and Time Series Analysis and Forecasting (8 papers). Olga Valenzuela is often cited by papers focused on Fuzzy Logic and Control Systems (20 papers), Neural Networks and Applications (18 papers) and Time Series Analysis and Forecasting (8 papers). Olga Valenzuela collaborates with scholars based in Spain, United States and Germany. Olga Valenzuela's co-authors include Ignacio Rojas, H. Pomares, Luis Javier Herrera, Fernando Rojas, Alberto Guillén, M. Pasadas, A. Prieto, Blanca L. Delgado‐Márquez, Oresti Baños and Jesús González and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Olga Valenzuela

80 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Olga Valenzuela Spain 18 462 177 163 157 133 84 1.1k
Fernando Rojas Spain 15 353 0.8× 145 0.8× 113 0.7× 125 0.8× 122 0.9× 68 866
Junkai Ji China 20 742 1.6× 141 0.8× 122 0.7× 227 1.4× 76 0.6× 68 1.2k
Michael G. Madden Ireland 16 611 1.3× 135 0.8× 207 1.3× 104 0.7× 87 0.7× 65 1.3k
Pedro J. García-Laencina Spain 12 845 1.8× 99 0.6× 201 1.2× 137 0.9× 116 0.9× 20 1.7k
Chieh-Jen Wang Taiwan 6 923 2.0× 121 0.7× 261 1.6× 115 0.7× 105 0.8× 19 1.7k
Jiwen Dong China 12 474 1.0× 139 0.8× 233 1.4× 133 0.8× 43 0.3× 53 1.1k
Derya Avcı Türkiye 19 500 1.1× 199 1.1× 305 1.9× 104 0.7× 60 0.5× 47 1.3k
Qun Dai China 20 676 1.5× 161 0.9× 218 1.3× 220 1.4× 40 0.3× 80 1.2k
Zheng Tang Japan 22 1.2k 2.5× 158 0.9× 260 1.6× 300 1.9× 132 1.0× 167 2.0k
Pritpal Singh India 24 458 1.0× 518 2.9× 198 1.2× 230 1.5× 92 0.7× 68 1.5k

Countries citing papers authored by Olga Valenzuela

Since Specialization
Citations

This map shows the geographic impact of Olga Valenzuela'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 Olga Valenzuela with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Olga Valenzuela more than expected).

Fields of papers citing papers by Olga Valenzuela

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Olga Valenzuela. 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 Olga Valenzuela. The network helps show where Olga Valenzuela may publish in the future.

Co-authorship network of co-authors of Olga Valenzuela

This figure shows the co-authorship network connecting the top 25 collaborators of Olga Valenzuela. A scholar is included among the top collaborators of Olga Valenzuela 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 Olga Valenzuela. Olga Valenzuela is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Valenzuela, Olga, Fernando Rojas, Luis Javier Herrera, H. Pomares, & Ignacio Rojas. (2023). Theory and Applications of Time Series Analysis and Forecasting. 1 indexed citations
2.
Rojas, Ignacio, et al.. (2023). Novel methodology for detecting and localizing cancer area in histopathological images based on overlapping patches. Computers in Biology and Medicine. 168. 107713–107713. 5 indexed citations
3.
Valenzuela, Olga, Fernando Rojas, Luis Javier Herrera, H. Pomares, & Ignacio Rojas. (2023). New Developments in Time Series and Forecasting, ITISE-2023. SHILAP Revista de lepidopterología. 101–101.
4.
Valenzuela, Olga, et al.. (2023). Advances and challenges in Bioinformatics and Biomedical Engineering: IWBBIO 2020. BMC Bioinformatics. 24(S2). 361–361. 1 indexed citations
5.
Castillo-Secilla, Daniel, Juan Manuel Gálvez, Francisco Carrillo‐Pérez, et al.. (2022). Comprehensive Pan-cancer Gene Signature Assessment through theImplementation of a Cascade Machine Learning System. Current Bioinformatics. 18(1). 40–54. 1 indexed citations
6.
Rojas, Fernando, et al.. (2022). Determination of the Severity and Percentage of COVID-19 Infection through a Hierarchical Deep Learning System. Journal of Personalized Medicine. 12(4). 535–535. 9 indexed citations
7.
Valenzuela, Olga, Fernando Rojas, Ignacio Rojas, & Peter Glösekötter. (2020). Main findings and advances in bioinformatics and biomedical engineering- IWBBIO 2018. BMC Bioinformatics. 21(S7). 153–153.
8.
Gálvez, Juan Manuel, Daniel Castillo-Secilla, Luis Javier Herrera, et al.. (2019). Towards Improving Skin Cancer Diagnosis by Integrating Microarray and RNA-Seq Datasets. IEEE Journal of Biomedical and Health Informatics. 24(7). 2119–2130. 21 indexed citations
9.
Valenzuela, Olga, et al.. (2018). Wearable Intelligent System for the Diagnosis of Cardiac Diseases Working in Real Time and with Low Energy Cost. SHILAP Revista de lepidopterología. 513–513. 1 indexed citations
10.
González, Jesús, et al.. (2017). Statistical Analysis of the Main Configuration Parameters of the Network Dynamic and Adaptive Radio Protocol (DARP). Sensors. 17(7). 1502–1502. 1 indexed citations
11.
Rojas, Ignacio, et al.. (2013). Innovative Strategy to Improve Precision and to Save Power of a Real-Time Control Process Using an Online Adaptive Fuzzy Logic Controller. Advances in Fuzzy Systems. 2013. 1–16. 3 indexed citations
12.
13.
Pomares, H., et al.. (2011). An enhanced clustering function approximation technique for a radial basis function neural network. Mathematical and Computer Modelling. 55(3-4). 286–302. 13 indexed citations
14.
Pomares, H., et al.. (2005). Hierarchical Structure for function approximation using radial basis function. International Conference on Applied Mathematics. 228–233. 1 indexed citations
15.
Valenzuela, Olga, et al.. (2005). Automatic classification of prostate cancer using pseudo-gaussian radial basis function neural network. The European Symposium on Artificial Neural Networks. 145–150. 3 indexed citations
16.
Herrera, Luis Javier, et al.. (2004). MultiGrid-Based Fuzzy Systems for Time Series Forecasting: Overcoming the curse of dimensionality. The European Symposium on Artificial Neural Networks. 14. 127–132. 2 indexed citations
17.
Rojas, Ignacio, et al.. (1998). What are the main factors involved in the design of a Radial Basis Function Network. The European Symposium on Artificial Neural Networks. 1–6. 4 indexed citations
18.
Rojas, Ignacio, Olga Valenzuela, M. Anguita, & A. Prieto. (1998). Analysis of the operators involved in the definition of the implication functions and in the fuzzy inference process. International Journal of Approximate Reasoning. 19(3-4). 367–389. 18 indexed citations
19.
Valenzuela, Olga, Gregory G. Deierlein, & Richard N. White. (1993). A Structural Engineering Education Image Database. 447–454. 2 indexed citations
20.
Valenzuela, Olga, Gregory G. Deierlein, & Richard N. White. (1992). Use of Multimedia in a Sophomore Design Course. 229–236. 1 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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