Modelos basados en big data e inteligencia artificial generativa para la optimización de la educación, logística portuaria y atención primaria

Ricardo Manuel Candanedo Yau; Belkis Ichelle Camaño Lasso; Oneida del Carmen Garay Menasho

doi:10.70625/rlce/614

Authors

Ricardo Manuel Candanedo Yau Universidad de Panamá Author
Belkis Ichelle Camaño Lasso Universidad de Panamá Author
Oneida del Carmen Garay Menasho Universidad de Panamá Author https://orcid.org/0009-0002-4412-5422

DOI:

https://doi.org/10.70625/rlce/614

Keywords:

Atención primaria de salud, Big data, Educación, Inteligencia artificial, Logística

Abstract

El estudio analizó la aplicación de modelos basados en Big Data e Inteligencia Artificial Generativa (IAG) para la optimización de tres sectores estratégicos: educación, logística portuaria y atención primaria de salud. Se adoptó un enfoque metodológico mixto, combinando revisión documental, análisis de datos y modelado predictivo, con el propósito de identificar patrones, mejorar la toma de decisiones y aumentar la eficiencia operativa. Los resultados evidenciaron que la integración de algoritmos generativos y analítica avanzada permitió personalizar procesos educativos, optimizar la gestión de cadenas logísticas portuarias y fortalecer la capacidad de respuesta en servicios de salud primaria. Asimismo, se observó una mejora significativa en la predicción de comportamientos, la asignación de recursos y la reducción de tiempos operativos. El estudio concluyó que el uso estratégico de estas tecnologías emergentes contribuyó a la transformación digital sostenible de los sectores analizados, destacando la importancia de su implementación ética, segura y contextualizada.

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