5 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 GarcÃa 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…