Inteligencia artificial aplicada al análisis de imágenes histológicas para apoyo al diagnóstico: una revisión sistemática de la evidencia 2025-2026
Palabras clave:
Inteligencia artificial; histopatología; diagnóstico; aprendizaje profundo; revisión sistemática.Resumen
La inteligencia artificial (IA) aplicada a imágenes histológicas digitalizadas ha evolucionado rápidamente hacia tareas diagnósticas complejas. El objetivo de este trabajo es sintetizar la evidencia publicada entre 2025 y 2026 sobre aplicaciones de IA en histopatología diagnóstica. Como parte de la metodología se utilizó la revisión sistemática según PRISMA 2020 en PubMed, Google Académico y ScienceDirect, incluyendo estudios originales con imágenes histológicas digitalizadas para diagnóstico, clasificación o estratificación clínica. Se incluyeron 22 estudios, con predominio de patología oncológica (tracto gastrointestinal, mama, sistema nervioso central). Las arquitecturas de IA evolucionaron desde redes neuronales convolucionales hacia aprendizaje multi-instancia, transformers y foundation models. Más de la mitad reportó validación externa. Las métricas principales fueron AUROC, accuracy e índices de concordancia. La IA en patología digital muestra creciente sofisticación, pero persiste heterogeneidad metodológica que limita su implementación clínica generalizada.
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Derechos de autor 2026 Adán Joel Villanueva Sosa
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