Palabras clave
Inteligencia artificial
Sistemas inteligentes
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Resumen
Objetivo: Analizar aplicaciones, percepciones de usuarios, barreras e implicaciones éticas de la Inteligencia Artificial (IA) en la Atención Primaria de Salud (APS), proponiendo estrategias de integración segura y equitativa. Métodos: Revisión integradora con recolección de datos en bases científicas (2020-2025). El objeto comprende la producción global sobre IA en APS, utilizando protocolo estructurado con descriptores controlados (MeSH/DeCS) y criterios de inclusión temáticos. Resultados: Los resultados revelan una paradoja de madurez: mientras oftalmología y dermatología alcanzan precisión técnica avanzada, la integración asistencial sigue fragmentada por una "especialización contextual". El Norte Global automatiza la eficiencia administrativa, mientras el Sur Global usa la IA como ecualizador de acceso vía leapfrogging tecnológico. Se identificó un "optimismo cauteloso": profesionales enfrentan el dilema del deskilling y la deshumanización del vínculo, mientras pacientes priorizar la celeridad diagnóstica. Interoperabilidad, calidad de datos y gobernanza emergen como cuellos de botella críticos que impiden la transición definitiva de la validación in silico al mundo real. Consideraciones finales: El punto fuerte es la síntesis multidimensional inédita que integra evidencias técnicas con dimensiones socioculturales y éticas de la APS. La limitación reside en la exclusión de innovaciones bajo paywalls.
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