Document-level adverse drug reaction event extraction on electronic health records in Spanish

  1. Sara Santiso
  2. Arantza Casillas
  3. Alicia Pérez
  4. Maite Oronoz
  5. Koldo Gojenola
Revista:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Año de publicación: 2016

Número: 56

Páginas: 49-56

Tipo: Artículo

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Otras publicaciones en: Procesamiento del lenguaje natural

Resumen

Presentamos un sistema de extracción de Reacciones Adversas a Medicamentos (RAMs) para Informes Médicos Electrónicos escritos en español. El objetivo del sistema es asistir a expertos en farmacia cuando tienen que decidir si un paciente padece o no una o más RAMs. El núcleo del sistema es un modelo predictivo inferido de un corpus etiquetado manualmente, que cuenta con características semánticas y sintácticas. Este modelo es capaz de extraer RAMs de parejas enfermedad-medicamento en un informe dado. Finalmente, las RAMs extraídas automáticamente son post-procesadas usando un heurístico para presentar la información de una forma compacta. Esta fase ofrece los medicamentos y enfermedades del documento con su frecuencia, y también une las parejas relacionadas como RAMs. En resumen, el sistema no sólo presenta las RAMs en el texto sino que también da información concisa a petición de los expertos en farmacia (los usuarios potenciales del sistema).

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Fuente de los datos: Dialnet