4 citations · 6 across the 8 of their papers we have counts for
8 papers
MIRA-Ev:A Benchmark for Granular Evidence Detection and Relational Reasoning in Clinical Exams
Iker De la Iglesia, Johanna Ramirez-Romero, Jose Maria Villa-Gonzalez +3
Clinical NLP evaluation remains dominated by multiple-choice question answering (MCQA), which scores only final-answer accuracy and cannot detect when a model reaches the correct d…
To Adapt or not to Adapt, Rethinking the Value of Medical Knowledge-Aware Large Language Models
Ane G. Domingo-Aldama, Iker De La Iglesia, Maitane Urruela +2
BACKGROUND: Recent studies have shown that domain-adapted large language models (LLMs) do not consistently outperform general-purpose counterparts on standard medical benchmarks, r…
Automating Early Disease Prediction Via Structured and Unstructured Clinical Data
Ane G Domingo-Aldama, Marcos Merino Prado, Alain García Olea +3
This study presents a fully automated methodology for early prediction studies in clinical settings, leveraging information extracted from unstructured discharge reports. The propo…
ArgHiTZ at ArchEHR-QA 2025: A Two-Step Divide and Conquer Approach to Patient Question Answering for Top Factuality
Adrián Cuadrón, Aimar Sagasti, Maitane Urruela +5
This work presents three different approaches to address the ArchEHR-QA 2025 Shared Task on automated patient question answering. We introduce an end-to-end prompt-based baseline a…
Ali-AUG: Innovative Approaches to Labeled Data Augmentation using One-Step Diffusion Model
Ali Hamza, Aizea Lojo, Adrian Núñez-Marcos +1
This paper introduces Ali-AUG, a novel single-step diffusion model for efficient labeled data augmentation in industrial applications. Our method addresses the challenge of limited…
Explanatory Argument Extraction of Correct Answers in Resident Medical Exams
Iakes Goenaga, Aitziber Atutxa, Koldo Gojenola +2
Developing the required technology to assist medical experts in their everyday activities is currently a hot topic in the Artificial Intelligence research field. Thus, a number of…
EriBERTa: A Bilingual Pre-Trained Language Model for Clinical Natural Language Processing
Iker de la Iglesia, Aitziber Atutxa, Koldo Gojenola +1
The utilization of clinical reports for various secondary purposes, including health research and treatment monitoring, is crucial for enhancing patient care. Natural Language Proc…
HiTZ@Antidote: Argumentation-driven Explainable Artificial Intelligence for Digital Medicine
Rodrigo Agerri, Iñigo Alonso, Aitziber Atutxa +9
Providing high quality explanations for AI predictions based on machine learning is a challenging and complex task. To work well it requires, among other factors: selecting a prope…