Tendencias de adopción de inteligencia artificial en la salud en Barranquilla
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Fecha
2022
Autores
González Meza, Carlos Mario
Pabón Pertuz, Carlos Manuel
Acuña Arévalo, Kevin Manuel
Lozano Vergara, Juan José
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Ediciones Universidad Simón Bolívar
Facultad de Ingenierías
Facultad de Ingenierías
Resumen
Las aplicaciones de Inteligencia Artificial se han multiplicado en los últimos años a través de todos los sectores de la actividad humana. En el sector salud este crecimiento no ha sido menos intenso o diverso, pero no hay suficiente información sobre el ritmo y orientación de estas tecnologías en el Atlántico. Esta investigación buscó caracterizar la evolución de esas tecnologías, haciendo énfasis en los casos locales, así como caracterizar, tanto la adopción de ellas en Instituciones Prestadoras de Servicios de Salud, como la relación existente entre esa tendencia de adopción y la evolución de los proyectos de investigación por parte de Centros y Grupos de Investigación regionales. La reducida cantidad de Instituciones e Investigadores directamente relacionados con el tema obligó a la producción de datos primarios a través de una encuesta complementaria diseñada para esos dos grupos de actores. Del análisis de esa información se concluye que hay una clara preferencia por aplicaciones de I.A. en el área de diagnóstico, tanto histórica, como en el futuro previsible a cinco años, tanto en las Instituciones como en los Investigadores. En el caso de estos últimos, esa tendencia ha sido orientada desde las prioridades nacionales definidas por las entidades financiadores de proyectos de Investigación, lo que puede ser una ventaja, al estimular el crecimiento coherente de estas tecnologías a nivel nacional, pero a la vez un riesgo si cambios en el gobierno central reorientan esas prioridades y afectan el financiamiento de este tipo de proyectos.
Artificial Intelligence applications have multiplied in recent years across all sectors of human activity. In the health sector this growth has not been less intense or diverse, but there is not enough information on the pace and orientation of these technologies in the Atlantic. This research sought to characterize the evolution of these technologies, with emphasis on local cases, as well as to characterize both the adoption of these technologies in Health Service Providing Institutions and the relationship between this adoption trend and the evolution of research projects by regional Research Centers and Groups. The small number of Institutions and Researchers directly related to the topic made it necessary to produce primary data through a complementary survey designed for these two groups of actors. From the analysis of this information, it can be concluded that there is a clear preference for A.I. applications in the diagnostic area, both historically and in the foreseeable future in five years, both in the Institutions and in the Researchers. In the case of the latter, this trend has been oriented from the national priorities defined by the entities financing research projects, which can be an advantage, by stimulating the coherent growth of these technologies at the national level, but at the same time a risk if changes in the central government reorient these priorities and affect the financing of this type of projects.
Artificial Intelligence applications have multiplied in recent years across all sectors of human activity. In the health sector this growth has not been less intense or diverse, but there is not enough information on the pace and orientation of these technologies in the Atlantic. This research sought to characterize the evolution of these technologies, with emphasis on local cases, as well as to characterize both the adoption of these technologies in Health Service Providing Institutions and the relationship between this adoption trend and the evolution of research projects by regional Research Centers and Groups. The small number of Institutions and Researchers directly related to the topic made it necessary to produce primary data through a complementary survey designed for these two groups of actors. From the analysis of this information, it can be concluded that there is a clear preference for A.I. applications in the diagnostic area, both historically and in the foreseeable future in five years, both in the Institutions and in the Researchers. In the case of the latter, this trend has been oriented from the national priorities defined by the entities financing research projects, which can be an advantage, by stimulating the coherent growth of these technologies at the national level, but at the same time a risk if changes in the central government reorient these priorities and affect the financing of this type of projects.
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Inteligencia artificial, Tecnología en Salud, Medicina, Machine learning, Redes neuronales, Aplicaciones de IA, Artificial intelligence, Health technology, Medicine, Neural networks, AI applications