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Evaluación de la calidad metodológica de las revisiones sistemáticas utilizando grandes modelos de lenguaje

Bowen Yao1,2, Onuralp Ergun1,2, Maylynn Ding2

  • 1Minneapolis VA Healthcare System, Minneapolis, MN, United States.

Canadian Urological Association journal = Journal de l'Association des urologues du Canada
|September 2, 2025
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Resumen

Los modelos generativos de lenguaje grande (LLM) muestran potencial para evaluar la calidad de las revisiones sistemáticas (SR). Con instrucciones específicas, GPT logró una precisión del 93% en la evaluación de la calidad, lo que indica capacidades de evaluación eficientes y confiables.

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Área de la Ciencia:

  • La inteligencia artificial en la medicina
  • La informática médica
  • Investigación en Urología

Sus antecedentes:

  • La evaluación de la calidad metodológica de las revisiones sistemáticas es crucial para la medicina basada en la evidencia.
  • Los modelos generativos de lenguaje grande (LLM) ofrecen potencial para automatizar tareas analíticas complejas.

Objetivo del estudio:

  • Evaluar la exactitud de los LLM generativos en la evaluación de la calidad metodológica de los SR urológicos.
  • Para comparar la evaluación de la calidad basada en LLM con la evaluación de expertos humanos.

Principales métodos:

  • Se evaluaron 114 SR urológicos por expertos humanos y un modelo personalizado de GPT.
  • El GPT se sometió a tres iteraciones de evaluación de tiro cero y a un ensayo mejorado utilizando el impulso de la cadena de pensamiento.
  • Las métricas de rendimiento incluían precisión, sensibilidad, especificidad y puntuación F1 frente a los juicios humanos.

Principales resultados:

  • El GPT logró un 75% de congruencia general con los revisores humanos, con un 77% para los criterios críticos.
  • La puntuación promedio de F1 fue de 0,66 y la validez interna fue alta, del 85%.
  • Mejora de la congruencia de los criterios críticos al 91% y de la precisión general al 93%.

Conclusiones:

  • Los LLM generativos demuestran una capacidad prometedora para la evaluación eficiente y precisa de la calidad de los SR en urología.
  • Las herramientas basadas en LLM pueden racionalizar el proceso de revisión y apoyar la síntesis de evidencia.