Search Results - "Atutxa, Aitziber"

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  1. 1

    Advances in monolingual and crosslingual automatic disability annotation in Spanish by Goenaga, Iakes, Andres, Edgar, Gojenola, Koldo, Atutxa, Aitziber

    Published in BMC bioinformatics (26-06-2023)
    “…Unlike diseases, automatic recognition of disabilities has not received the same attention in the area of medical NLP. Progress in this direction is hampered…”
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    Journal Article
  2. 2

    Towards a top-down approach for an automatic discourse analysis for Basque: Segmentation and Central Unit detection tool by Atutxa, Aitziber, Bengoetxea, Kepa, Diaz de Ilarraza, Arantza, Iruskieta, Mikel

    Published in PloS one (04-09-2019)
    “…Lately, discourse structure has received considerable attention due to the benefits its application offers in several NLP tasks such as opinion mining,…”
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    Journal Article
  3. 3

    Explanatory argument extraction of correct answers in resident medical exams by Goenaga, Iakes, Atutxa, Aitziber, Gojenola, Koldo, Oronoz, Maite, Agerri, Rodrigo

    Published in Artificial intelligence in medicine (01-11-2024)
    “…Developing technology to assist medical experts in their everyday decision-making is currently a hot topic in the field of Artificial Intelligence (AI). This…”
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    Journal Article
  4. 4

    Machine Learning Approaches on Diagnostic Term Encoding With the ICD for Clinical Documentation by Atutxa, Aitziber, Perez, Alicia, Casillas, Arantza

    “…This work focuses on data mining applied to the clinical documentation domain. Diagnostic terms (DTs) are used as keywords to retrieve valuable information…”
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    Journal Article
  5. 5

    A section identification tool: Towards HL7 CDA/CCR standardization in Spanish discharge summaries by Goenaga, Iakes, Lahuerta, Xabier, Atutxa, Aitziber, Gojenola, Koldo

    Published in Journal of biomedical informatics (01-09-2021)
    “…Nowadays, with the digitalization of healthcare systems, huge amounts of clinical narratives are available. However, despite the wealth of information…”
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    Journal Article
  6. 6

    Interpretable deep learning to map diagnostic texts to ICD-10 codes by Atutxa, Aitziber, de Ilarraza, Arantza Díaz, Gojenola, Koldo, Oronoz, Maite, Perez-de-Viñaspre, Olatz

    “…•Automatic extraction of morbid disease or conditions contained in death certificates is extremely useful for standardization, alleviating and smoothing human…”
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    Journal Article
  7. 7

    An open source corpus and automatic tool for section identification in Spanish health records by de la Iglesia, Iker, Vivó, María, Chocrón, Paula, Maeztu, Gabriel de, Gojenola, Koldo, Atutxa, Aitziber

    Published in Journal of biomedical informatics (01-09-2023)
    “…Electronic Clinical Narratives (ECNs) store valuable individual’s health information. However, there are few available open-source data. Besides, ECNs can be…”
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    Journal Article
  8. 8

    Inferred joint multigram models for medical term normalization according to ICD by Pérez, Alicia, Atutxa, Aitziber, Casillas, Arantza, Gojenola, Koldo, Sellart, Álvaro

    “…[Display omitted] •Health records comprise valuable information written in a spontaneous register.•Matching spontaneous terms in standard ICD terminology is…”
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    Journal Article
  9. 9

    Ali-AUG: Innovative Approaches to Labeled Data Augmentation using One-Step Diffusion Model by Hamza, Ali, Lojo, Aizea, Núñez-Marcos, Adrian, Atutxa, Aitziber

    Published 24-10-2024
    “…This paper introduces Ali-AUG, a novel single-step diffusion model for efficient labeled data augmentation in industrial applications. Our method addresses the…”
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    Journal Article
  10. 10

    Explanatory Argument Extraction of Correct Answers in Resident Medical Exams by Goenaga, Iakes, Atutxa, Aitziber, Gojenola, Koldo, Oronoz, Maite, Agerri, Rodrigo

    Published 01-12-2023
    “…Developing the required technology to assist medical experts in their everyday activities is currently a hot topic in the Artificial Intelligence research…”
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    Journal Article
  11. 11

    EriBERTa: A Bilingual Pre-Trained Language Model for Clinical Natural Language Processing by de la Iglesia, Iker, Atutxa, Aitziber, Gojenola, Koldo, Barrena, Ander

    Published 12-06-2023
    “…The utilization of clinical reports for various secondary purposes, including health research and treatment monitoring, is crucial for enhancing patient care…”
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    Journal Article
  12. 12

    HiTZ@Antidote: Argumentation-driven Explainable Artificial Intelligence for Digital Medicine by Agerri, Rodrigo, Alonso, Iñigo, Atutxa, Aitziber, Berrondo, Ander, Estarrona, Ainara, Garcia-Ferrero, Iker, Goenaga, Iakes, Gojenola, Koldo, Oronoz, Maite, Perez-Tejedor, Igor, Rigau, German, Yeginbergenova, Anar

    Published 09-06-2023
    “…Providing high quality explanations for AI predictions based on machine learning is a challenging and complex task. To work well it requires, among other…”
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    Journal Article
  13. 13

    Medical mT5: An Open-Source Multilingual Text-to-Text LLM for The Medical Domain by García-Ferrero, Iker, Agerri, Rodrigo, Salazar, Aitziber Atutxa, Cabrio, Elena, de la Iglesia, Iker, Lavelli, Alberto, Magnini, Bernardo, Molinet, Benjamin, Ramirez-Romero, Johana, Rigau, German, Villa-Gonzalez, Jose Maria, Villata, Serena, Zaninello, Andrea

    Published 11-04-2024
    “…Research on language technology for the development of medical applications is currently a hot topic in Natural Language Understanding and Generation. Thus, a…”
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    Journal Article
  14. 14

    Patrixa: a unification-based parser for Basque and its aplication to the automatic analysis of verbs by Izaskun Aldezabal, M.ª Jesús Aranzabe, Aitziber Atutxa, Koldo Gojenola, Kepa Sarasola

    “…In this paper we describe a computational grammar for Basque, and the first results obtained using it in the process of automatically acquiring…”
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  15. 15

    Learning argument/adjunct distinction for Basque by Izaskun Aldezabal, M.ª Jesús Aranzabe, Koldo Gojenola, Kepa Sarasola, Aitziber Atutxa

    “…This paper presents experiments performed on lexical knowledge acquisition in the form of verbal argumental information. The system obtains the data from raw…”
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