Machine learning models in health prevention and promotion and labor productivity: A co-word analysis

Autores/as

  • Sergio Arturo Dominguez Miranda Universidad Panamericana
  • Roman Rodriguez Aguilar Universidad panamericana

DOI:

https://doi.org/10.47909/ijsmc.85

Palabras clave:

co-word analysis, research trends, bibliometrics, machine learning models, health prevention and promotion, labor productivity

Resumen

La salud es elemento vital para el desarrollo de diversas habilidades y potenciar la economía de los países. El impacto en la productividad por parte de los empleados en las empresas puede tener un beneficio relevante tanto económico como reputacional, sin embargo, la forma de abordaje puede ser complicada si no tenemos herramientas de análisis como los generados a partir de modelos de machine Learning, el propósito de esta investigación es la realización de un análisis bibliográfico respecto a investigaciones enfocadas en productividad de las empresas a partir de los elementos de salud y con análisis de machine Learning utilizando métodos de análisis estadístico, relaciones y análisis histórico con base a la terminología utilizada en palabras clave y los resúmenes de la, se encontraron 87 artículos relevantes desde el 2008 a la fecha con un crecimiento anual promedio de 23.25%, se encontraron los principales algoritmos utilizados de machine Learning, los principales enfoques de investigación derivado del análisis de mapeo temático, los principales autores que han escrito así como referenciados y el uso de componentes principales mostró los principales términos con un 71.92% de variabilidad. Se espera que esta investigación pueda dar norte a futuras investigaciones para enfoque en productividad empresarial y el beneficio para los empleados.

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Citas

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Iberoamerican Journal of Science Measurement and Communication

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2024-04-07

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Dominguez Miranda, S. A., & Rodriguez Aguilar , R. (2024). Machine learning models in health prevention and promotion and labor productivity: A co-word analysis. Iberoamerican Journal of Science Measurement and Communication, 4(1), 1–16. https://doi.org/10.47909/ijsmc.85

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Vol. 4 Núm. 1 (2024): Iberoamerican Journal of Science Measurement and Communication

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Artículo original

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Derechos de autor 2024 Sergio Arturo Dominguez Miranda, Roman Rodriguez Aguilar

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