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IA Explicable para la Atención Médica

Yupei Li1, Qiyang Sun1, Alican Akman1

  • 1GLAM - Group on Language, Audio, & Music, Imperial College London, UK.

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|February 23, 2026
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Este resumen es generado por máquina.

La IA explicable (XAI) es crucial para aplicaciones de atención médica confiables. La XAI mejora la transparencia en los modelos de inteligencia artificial (IA), mejorando las decisiones clínicas y la confianza del paciente.

Palabras clave:
aplicación de IAInteligencia ArtificialSalud DigitalIA ExplicableAtención Médica

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Last Updated: Feb 24, 2026

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Área de la Ciencia:

  • Ciencias de la Computación; Inteligencia Artificial; Tecnología de la Salud

Sus antecedentes:

  • La integración de la inteligencia artificial (IA) en la atención médica avanza rápidamente, impactando el diagnóstico, el tratamiento y la atención al paciente.
  • Los modelos de IA complejos a menudo carecen de transparencia, lo que plantea riesgos en la toma de decisiones médicas de alto riesgo.
  • La explicabilidad es vital para la toma de decisiones clínicas informadas y la confianza del paciente en la IA.

Objetivo del estudio:

  • Introducir los conceptos fundamentales de la IA explicable (XAI).
  • Analizar las metodologías de XAI para mejorar la interpretabilidad de los modelos de IA en la atención médica.
  • Discutir las aplicaciones de XAI en diversas modalidades de datos de atención médica.

Principales métodos:

  • Revisión de los conceptos fundamentales de la IA explicable (XAI).
  • Análisis de metodologías prominentes para mejorar la interpretabilidad de los modelos de IA.
  • Examen de las aplicaciones de XAI en datos médicos de series temporales, texto, imágenes y audio.

Principales resultados:

  • La XAI proporciona una transparencia esencial para los profesionales de la salud y los pacientes.
  • La XAI aborda desafíos únicos en diversos tipos de datos médicos.
  • Se identificaron metodologías prominentes de XAI aplicables a dominios de atención médica.

Conclusiones:

  • La XAI es fundamental para la implementación segura y eficaz de la IA en la atención médica.
  • Se discutieron las limitaciones y desafíos actuales en la implementación de XAI en la atención médica.
  • Se identificaron prometedoras direcciones de investigación futuras para mejorar la confiabilidad de la IA en la atención médica.