Maite Oronoz

750 total citations
51 papers, 378 citations indexed

About

Maite Oronoz is a scholar working on Artificial Intelligence, Molecular Biology and Language and Linguistics. According to data from OpenAlex, Maite Oronoz has authored 51 papers receiving a total of 378 indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Artificial Intelligence, 27 papers in Molecular Biology and 6 papers in Language and Linguistics. Recurrent topics in Maite Oronoz's work include Natural Language Processing Techniques (34 papers), Topic Modeling (29 papers) and Biomedical Text Mining and Ontologies (27 papers). Maite Oronoz is often cited by papers focused on Natural Language Processing Techniques (34 papers), Topic Modeling (29 papers) and Biomedical Text Mining and Ontologies (27 papers). Maite Oronoz collaborates with scholars based in Spain, Sweden and United States. Maite Oronoz's co-authors include Koldo Gojenola, Arantza Casillas, Alicia Pérez, Arantza Díaz de Ilarraza, Rebecka Weegar, Rodrigo Agerri, Hercules Dalianis, Gorka Labaka, Montse Maritxalar and Nerea Ezeiza and has published in prestigious journals such as Expert Systems with Applications, Journal of the American Medical Informatics Association and International Journal of Medical Informatics.

In The Last Decade

Maite Oronoz

48 papers receiving 348 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Maite Oronoz Spain	11	299	209	34	27	20	51	378
Koldo Gojenola Spain	12	377 1.3×	184 0.9×	45 1.3×	26 1.0×	24 1.2×	63	443
Yikun Guo United Kingdom	11	377 1.3×	351 1.7×	22 0.6×	14 0.5×	20 1.0×	24	466
Arantza Díaz de Ilarraza Spain	11	484 1.6×	114 0.5×	22 0.6×	13 0.5×	12 0.6×	109	547
Bryan Rink United States	12	445 1.5×	174 0.8×	14 0.4×	5 0.2×	10 0.5×	20	487
Kai Hakala Finland	11	237 0.8×	257 1.2×	9 0.3×	18 0.7×	20 1.0×	19	377
Abdul Mateen Rajput Germany	5	225 0.8×	192 0.9×	14 0.4×	74 2.7×	76 3.8×	10	338
Martin Duneld Sweden	7	235 0.8×	156 0.7×	27 0.8×	35 1.3×	13 0.7×	14	280
Mourad Sarrouti United States	11	240 0.8×	121 0.6×	6 0.2×	22 0.8×	39 1.9×	23	286
Yueping Sun China	4	460 1.5×	323 1.5×	4 0.1×	7 0.3×	27 1.4×	9	526
Dongwook Shin United States	9	143 0.5×	198 0.9×	23 0.7×	6 0.2×	33 1.6×	17	283

Countries citing papers authored by Maite Oronoz

Since Specialization

Citations

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

Fields of papers citing papers by Maite Oronoz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maite Oronoz

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

All Works

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20 of 20 papers shown

Oronoz, Maite, et al.. (2024). Argument Mining in Data Scarce Settings: Cross-lingual Transfer and Few-shot Techniques. 11687–11699. 1 indexed citations

Oronoz, Maite, et al.. (2024). MedExpQA: Multilingual benchmarking of Large Language Models for Medical Question Answering. Artificial Intelligence in Medicine. 155. 102938–102938. 14 indexed citations

Gojenola, Koldo, et al.. (2024). Explanatory argument extraction of correct answers in resident medical exams. Artificial Intelligence in Medicine. 157. 102985–102985. 3 indexed citations

Labaka, Gorka, et al.. (2020). Ixamed’s submission description for WMT20 Biomedical shared task: benefits and limitations of using terminologies for domain adaptation. Empirical Methods in Natural Language Processing. 875–880.

Casillas, Arantza, Nerea Ezeiza, Víctor Fresno, et al.. (2018). IxaMed at CLEF eHealth 2018 Task 1: ICD10 Coding with a Sequence-to-Sequence Approach.. CLEF (Working Notes). 8 indexed citations

Weegar, Rebecka, Alicia Pérez, Hercules Dalianis, et al.. (2018). Ensembles for clinical entity extraction. Procesamiento del lenguaje natural. 60(60). 13–20. 3 indexed citations

Casillas, Arantza, et al.. (2016). Document-level adverse drug reaction event extraction on electronic health records in Spanish.. Procesamiento del lenguaje natural. 56(56). 49–56. 4 indexed citations

Weegar, Rebecka, Arantza Casillas, Arantza Díaz de Ilarraza, et al.. (2016). The impact of simple feature engineering in multilingual medical NER. International Conference on Computational Linguistics. 1–6. 1 indexed citations

Oronoz, Maite, Koldo Gojenola, Alicia Pérez, Arantza Díaz de Ilarraza, & Arantza Casillas. (2015). On the creation of a clinical gold standard corpus in Spanish: Mining adverse drug reactions. Journal of Biomedical Informatics. 56. 318–332. 63 indexed citations

10.

Casillas, Arantza, et al.. (2014). Adverse Drug Event prediction combining shallow analysis and machine learning. 85–89. 8 indexed citations

11.

Oronoz, Maite, et al.. (2013). A Finite-State Approach to Translate SNOMED CT Terms into Basque Using Medical Prefixes and Suffixes. 99–103. 2 indexed citations

12.

Casillas, Arantza, et al.. (2012). First Approaches on Spanish Medical Record Classification Using Diagnostic Term to Class Transduction. 60–64. 3 indexed citations

13.

Oronoz, Maite, et al.. (2010). First Steps in The Manual and Automatic Annotation of Clinical Notes in Spanish. Procesamiento del lenguaje natural. 45(45). 259–262. 1 indexed citations

14.

Uria, Larraitz, et al.. (2009). Determiner errors in Basque: analysis and automatic detection. Procesamiento del lenguaje natural. 41–48. 5 indexed citations

15.

Ilarraza, Arantza Díaz de, Koldo Gojenola, & Maite Oronoz. (2008). Detecting Erroneous Uses of Complex Postpositions in an Agglutinative Language. International Conference on Computational Linguistics. 43(2). 31–34. 10 indexed citations

16.

Aldabe, Itziar, et al.. (2005). Propuesta de una clasificación general y dinámica para la definición de errores. Revista de Psicodidáctica. 10(2). 47–59. 6 indexed citations

17.

Ilarraza, Arantza Díaz de, et al.. (2004). Abar-Hitz: An Annotation Tool for the Basque Dependency Treebank.. Language Resources and Evaluation. 4 indexed citations

18.

Ilarraza, Arantza Díaz de, et al.. (2002). The Design of a Digital Resource to Store the Knowledge of Linguistic Errors. 1 indexed citations

19.

Ilarraza, Arantza Díaz de, et al.. (2002). Construcción de un corpus etiquetado sintácticamente para el euskera. Procesamiento del lenguaje natural. 29(29). 5–11. 4 indexed citations

20.

Maritxalar, Montse, Arantza Díaz de Ilarraza, & Maite Oronoz. (1997). From Psycholinguistic Modelling of Interlanguage in Second Language Acquisition to a Computational Model. 50–59. 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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