Fernando Gómez

2.4k total citations
106 papers, 1.8k citations indexed

About

Fernando Gómez is a scholar working on Artificial Intelligence, Surgery and Epidemiology. According to data from OpenAlex, Fernando Gómez has authored 106 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Artificial Intelligence, 16 papers in Surgery and 15 papers in Epidemiology. Recurrent topics in Fernando Gómez's work include Natural Language Processing Techniques (24 papers), Topic Modeling (21 papers) and Semantic Web and Ontologies (20 papers). Fernando Gómez is often cited by papers focused on Natural Language Processing Techniques (24 papers), Topic Modeling (21 papers) and Semantic Web and Ontologies (20 papers). Fernando Gómez collaborates with scholars based in Spain, United States and Argentina. Fernando Gómez's co-authors include María Teresa Corcuera, Ángeles Domínguez‐Soto, Ángel L. Corbí, Paloma Sánchez‐Mateos, Elena Sierra‐Filardi, Amaya Puig‐Kröger, Bharath Chandrasekaran, Rafael Samaniego, Manohar Ratnam and María Luisa Caballero and has published in prestigious journals such as The Journal of Immunology, Hepatology and Cancer Research.

In The Last Decade

Fernando Gómez

95 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fernando Gómez Spain 20 380 357 343 235 230 106 1.8k
S.-C.B. Lo United States 20 470 1.2× 95 0.3× 180 0.5× 59 0.3× 96 0.4× 33 1.4k
Thomas Stehlé Germany 32 57 0.1× 397 1.1× 717 2.1× 265 1.1× 55 0.2× 106 2.7k
Xiaowen Liang United States 30 117 0.3× 265 0.7× 1.2k 3.5× 120 0.5× 63 0.3× 72 2.6k
Robert W. Dunstan United States 25 91 0.2× 292 0.8× 499 1.5× 279 1.2× 24 0.1× 88 2.0k
David S. Guttery United Kingdom 30 405 1.1× 227 0.6× 794 2.3× 63 0.3× 44 0.2× 65 2.7k
Tim Hulsen Netherlands 12 185 0.5× 153 0.4× 954 2.8× 61 0.3× 78 0.3× 28 1.9k
Mikael Huss Sweden 25 145 0.4× 148 0.4× 2.9k 8.4× 141 0.6× 82 0.4× 56 3.9k
Thorsten Forster United Kingdom 24 36 0.1× 570 1.6× 1.1k 3.2× 138 0.6× 130 0.6× 53 2.2k
Juan Carlos Silva United States 28 276 0.7× 43 0.1× 411 1.2× 102 0.4× 50 0.2× 86 2.7k
Claudio Lottaz Germany 21 121 0.3× 658 1.8× 1.6k 4.7× 48 0.2× 157 0.7× 33 3.0k

Countries citing papers authored by Fernando Gómez

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Gómez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fernando Gómez

This figure shows the co-authorship network connecting the top 25 collaborators of Fernando Gómez. A scholar is included among the top collaborators of Fernando Gómez 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 Fernando Gómez. Fernando Gómez 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.
Delfino, José M., Fernando Gómez, Cristina Ibarra, et al.. (2024). Soluplus® nanomicelles enhance IgG neutralizing properties against Shiga toxin type 2. Journal of Drug Delivery Science and Technology. 95. 105606–105606. 1 indexed citations
2.
Corcuera, María Teresa, Fernando Gómez, Rosa Rodríguez‐Pérez, et al.. (2018). Exploring tumourigenic potential of the parasite Anisakis: a pilot study. Parasitology Research. 117(10). 3127–3136. 13 indexed citations
3.
Gómez, Fernando, et al.. (2013). A New Set of Norms for Semantic Relatedness Measures. Journal of International Crisis and Risk Communication Research. 890–895. 22 indexed citations
4.
Corcuera, María Teresa, et al.. (2013). Morphological plasticity of Streptococcus oralis isolates for biofilm production, invasiveness, and architectural patterns. Archives of Oral Biology. 58(11). 1584–1593. 5 indexed citations
5.
Corcuera, María Teresa, Fernando Gómez, Pablo González, et al.. (2013). A rat model of intragastric infection with Anisakis spp. live larvae: histopathological study. Parasitology Research. 112(6). 2409–2411. 9 indexed citations
6.
Schwartz, H. Andrew, Fernando Gómez, & Lyle Ungar. (2012). Improving Supervised Sense Disambiguation with Web-Scale Selectors. International Conference on Computational Linguistics. 2423–2440. 1 indexed citations
7.
Gómez, Fernando, et al.. (2011). Evaluating a Semantic Network Automatically Constructed from Lexical Co-occurrence on a Word Sense Disambiguation Task. Journal of International Crisis and Risk Communication Research. 190–199.
8.
Schwartz, Hansen Andrew & Fernando Gómez. (2010). UCF-WS: Domain Word Sense Disambiguation Using Web Selectors. Journal of International Crisis and Risk Communication Research. 392–395. 1 indexed citations
9.
Puig‐Kröger, Amaya, Elena Sierra‐Filardi, Ángeles Domínguez‐Soto, et al.. (2009). Folate Receptor β Is Expressed by Tumor-Associated Macrophages and Constitutes a Marker for M2 Anti-inflammatory/Regulatory Macrophages. Cancer Research. 69(24). 9395–9403. 310 indexed citations
10.
Schwartz, Hansen Andrew, et al.. (2008). A Semantic Feature for Verbal Predicate and Semantic Role Labeling using SVMs. Journal of International Crisis and Risk Communication Research. 213–218. 2 indexed citations
11.
Sánchez‐Patán, Fernando, María‐Angeles Aller, Carmen Cuéllar, et al.. (2008). Mast cell inhibition by ketotifen reduces splanchnic inflammatory response in a portal hypertension model in rats. Experimental and Toxicologic Pathology. 60(4-5). 347–355. 13 indexed citations
12.
Gómez, Fernando. (2007). Semantic Interpretation and the Upper-Level Ontology of WordNet. Journal of Intelligent Systems. 16(2). 93–116. 1 indexed citations
13.
Sánchez‐Patán, Fernando, María‐Angeles Aller, María Teresa Corcuera, et al.. (2006). Enteropatía hipertensiva portal inflamatoria crónica en la rata. Cirugía Española. 80(3). 162–167. 5 indexed citations
14.
Gómez, Fernando, et al.. (2004). Valoración global del control de síntomas al final de la vida. Medicina Paliativa. 11(2). 79–82. 2 indexed citations
15.
Gómez, Fernando. (2001). Good Places and Non-Places in Colonial México: The Figure of Vasco de Quiroga. Utopian Studies. 14(2). 5 indexed citations
16.
Gómez, Fernando. (1998). Linking WordNet Verb Classes to Semantic Interpretation.. International Conference on Computational Linguistics. 8 indexed citations
17.
Gómez, Fernando, et al.. (1997). Simultaneous detection of antigens and specific DNA sequences of human papillomavirus in uterine cervical biopsy specimens. Description of a double-labelling technique.. PubMed. 41(4). 255–9. 1 indexed citations
18.
Gómez, Fernando, et al.. (1996). Semantic interpretation of nominalizations. Journal of International Crisis and Risk Communication Research. 1062–1068. 18 indexed citations
19.
Gómez, Fernando & Bharath Chandrasekaran. (1987). Knowledge organization and distribution for medical diagnosis. IEEE Press eBooks. 211–219. 24 indexed citations
20.
Chandrasekaran, B., Fernando Gómez, S. Mittal, & Jack W. Smith. (1979). An approach to medical diagnosis based on conceptual structures. International Joint Conference on Artificial Intelligence. 134–142. 45 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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