Hermenegildo Fabregat-rekin lankidetzan egindako argitalpenak (21)

2024

  1. NLP-UNED at eRisk 2024: Approximate Nearest Neighbors with Encoding Refinement for Early Detecting Signs of Anorexia

    CEUR Workshop Proceedings

  2. UNED-GELP at MentalRiskES 2024: Transformer-Based Encoders and Similarity Techniques for Early Risk Prediction of Mental Disorders

    CEUR Workshop Proceedings

2023

  1. A Re-labeling Approach Based on Approximate Nearest Neighbors for Identifying Gambling Disorders in Social Media

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. LSI_UNED at ClinAIS 2023: Transformer Models for Section Identification in Spanish Medical Reports

    CEUR Workshop Proceedings

  3. NLP-UNED at MentalRiskES 2023: Approximate Nearest Neighbors for Identifying Health Disorders

    CEUR Workshop Proceedings

  4. NLP-UNED-2 at eRisk 2023: Detecting Pathological Gambling in Social Media through Dataset Relabeling and Neural Networks

    CEUR Workshop Proceedings

  5. Negation-based transfer learning for improving biomedical Named Entity Recognition and Relation Extraction

    Journal of Biomedical Informatics, Vol. 138

2022

  1. UNED at PoliticEs 2022: Testing Approximate Nearest Neighbors and Spanish Language Models for Author Profiling in Political Ideology

    CEUR Workshop Proceedings

  2. UNED-NLP at eRisk 2022: Analyzing gambling disorders in Social Media using Approximate Nearest Neighbors

    CEUR Workshop Proceedings

2021

  1. A keyphrase-based approach for interpretable ICD-10 code classification of Spanish medical reports

    Artificial Intelligence in Medicine, Vol. 121

  2. LSI_UNED at CLEF eHealth2021: Exploring the effects of transfer learning in negation detection and entity recognition in clinical texts

    CEUR Workshop Proceedings

  3. NLP-UNED at eRisk 2021: Self-harm early risk detection with TF-IDF and linguistic features

    CEUR Workshop Proceedings

2020

  1. Understanding and Improving Disability Identification in Medical Documents

    IEEE Access, Vol. 8, pp. 155399-155408

2019

  1. De-identification through named entity recognition for medical document anonymization

    CEUR Workshop Proceedings

  2. Deep learning approach for negation trigger and scope recognition

    Procesamiento del lenguaje natural, Núm. 62, pp. 37-44

  3. Extending a deep learning approach for negation cues detection in Spanish

    CEUR Workshop Proceedings

  4. NLP uned at eHealth-KD challenge 2019 deep learning for named entity recognition and attentive relation extraction

    CEUR Workshop Proceedings

2018

  1. Deep learning approach for negation cues detection in Spanish

    CEUR Workshop Proceedings

  2. Deep neural models for extracting entities and relationships in the new RDD corpus relating disabilities and rare diseases

    Computer Methods and Programs in Biomedicine, Vol. 164, pp. 121-129

  3. Overview of the DIANN Task: Disability annotation task

    CEUR Workshop Proceedings