Extracción de datos clínicos basada en LLM: potenciales y desafíos

Paulina Seidl1, Marton Szep2,3, Sebastian Breden2

  • 1Klinik und Poliklinik für Orthopädie und Sportorthopädie, TUM Universitätsklinikum, Ismaninger Str. 22, 81675, München, Deutschland. paulina.seidl@tum.de.

PubMed
Resumen

Los modelos de lenguaje grandes (LLM) pueden extraer información de textos clínicos, reduciendo la carga de trabajo. La calidad de los prompts impacta significativamente la precisión de los LLM para la extracción confiable de datos clínicos.

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