Multicriteria Optimization of Language Models for Heart Failure With Preserved Ejection Fraction Symptom Detection in Spanish Electronic Health Records: Comparative Modeling Study.

Journal: Journal of medical Internet research
Published Date: Jul 17, 2025

Abstract

BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) is a major clinical manifestation of cardiac amyloidosis, a condition frequently underdiagnosed due to its nonspecific symptomatology. Electronic health records (EHRs) offer a promising avenue for supporting early symptom detection through natural language processing. However, identifying relevant clinical cues within unstructured narratives, particularly in Spanish, remains a significant challenge due to the scarcity of annotated corpora and domain-specific models. This study proposes and evaluates a Transformer-based natural language processing framework for automated detection of HFpEF-related symptoms in Spanish EHRs.

Authors

  • Jacinto Mata
    Higher Technical School of Engineering, University of Huelva, Huelva, Spain.
  • Victoria Pachón
    I²C Research Group, Universidad de Huelva, Huelva, 21007, Spain, +34 687862089.
  • Ana Manovel
    Cardiology Department, Juan Ramón Jiménez University Hospital, Multidisciplinary Amyloidosis Unit Huelva, Hospital Juan Ramón Jiménez, Huelva, Spain.
  • Manuel J Maña
    I²C Research Group, Universidad de Huelva, Huelva, 21007, Spain, +34 687862089.
  • Manuel de la Villa
    Departamento de Tecnologías de la Información, Universidad de Huelva, Carretera Huelva - La Rábida, 21071, Huelva, Spain.

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