Maite Oronoz

774 citations
62 papers · 521 · h-index 13

Impact in

Papers in

    • Natural Language Processing Techniques 40
    • Topic Modeling 32
    • Text Readability and Simplification 8
    • Semantic Web and Ontologies 3
    • Biomedical Text Mining and Ontologies 27

Maite Oronoz

58 papers receiving 469 citations

Peers

Maite Oronoz
Comparison fields: 5 of 56
  • Health Informatics 18
  • Toxicology 37
  • Artificial Intelligence 364
  • Health Information Management 34
  • Molecular Biology 201
Replace Koldo Gojenola with:
Koldo Gojenola Spain
Yikun Guo United Kingdom
Bryan Rink United States
Mourad Sarrouti Morocco
Hiroshi Masuichi Japan
Rebecka Weegar Sweden
J E Rogers United Kingdom
O Bodenreider United States
Rob Koeling United Kingdom
Kai Hakala Finland
Maite Oronoz relative to Koldo Gojenola Spain Koldo Gojenola's profile →
Citations per field
00.5×1.5×
Koldo Gojenola · 1×
Citations per year

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-authors

The 20 scholars most cited alongside Maite Oronoz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Maite Oronoz Line = papers co-authored together Maite Oronoz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201568
2 201938
3 201636
4 201731
5 201328
6 200428
7 200625
8 202421
9 201917
10 201916
11 202013
12 201413
13 201512
14 201412
15 201410
16 200810
17 201810
18
Using Kybots for Extracting Events in Biomedical Texts
20119
19
IxaMed at CLEF eHealth 2018 Task 1: ICD10 Coding with a Sequence-to-Sequence Approach.
20188
20
Automatic Misogyny Identification Using Neural Networks.
20187

About Maite Oronoz

Maite Oronoz is a scholar working on Artificial Intelligence, Molecular Biology, Language and Linguistics, Information Systems and Toxicology, having authored 62 papers that have together received 521 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (40 papers), Topic Modeling (32 papers), Biomedical Text Mining and Ontologies (27 papers), Text Readability and Simplification (8 papers), Pharmacovigilance and Adverse Drug Reactions (4 papers), Basque language and culture studies (3 papers), Software Engineering Research (3 papers) and Semantic Web and Ontologies (3 papers). The work is most often cited by research in Health Informatics (18 citations), Toxicology (37 citations), Artificial Intelligence (364 citations), Health Information Management (34 citations) and Molecular Biology (201 citations). Maite Oronoz has collaborated with scholars based in Spain, Sweden and United States. Frequent co-authors include Koldo Gojenola, Arantza Casillas, Alicia Pérez, Arantza Díaz de Ilarraza, Rebecka Weegar, Rodrigo Agerri, Larraitz Uria, Gorka Labaka, Hercules Dalianis and Nerea Ezeiza. Their work appears in journals such as Journal of Biomedical Informatics, Artificial Intelligence in Medicine, Natural Language Engineering, Expert Systems with Applications and BMC Medical Informatics and Decision Making.

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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