Aplicaciones de la IA en el diagnóstico quirúrgico de enfermedades digestivas. Una revisión sistemática
DOI:
https://doi.org/10.26820/recimundo/9.(2).abril.2025.458-473Palabras clave:
Inteligencia Artificial, Diagnóstico, Enfermedades Gastrointestinales, Cirugía, Revisión SistemáticaResumen
Antecedentes/Objetivo: Las enfermedades digestivas representan una carga significativa para la salud global. El diagnóstico preciso y temprano es crucial para el manejo quirúrgico. La inteligencia artificial (IA) ofrece herramientas prometedoras para mejorar esta precisión. El objetivo de esta revisión sistemática es evaluar la evidencia actual sobre la aplicación de la IA en el diagnóstico quirúrgico de enfermedades digestivas. Métodos: Se realizaron búsquedas exhaustivas en PubMed, Scopus, Web of Science y Cochrane Library desde enero de 2010 hasta mayo de 2025. Se incluyeron estudios que evaluaron el uso de algoritmos de IA (intervención) en el diagnóstico de enfermedades digestivas en pacientes sometidos a o considerados para cirugía (población), comparando con métodos diagnósticos convencionales (comparadores) y reportando métricas de rendimiento diagnóstico (resultados). Se consideraron estudios observacionales y experimentales (diseño). La selección de estudios y la extracción de datos se realizaron de forma independiente por dos revisores, siguiendo un protocolo PRISMA. Resultados: Se incluyeron 25 estudios. Los hallazgos principales demuestran que la IA, particularmente las redes neuronales convolucionales y los modelos de aprendizaje profundo, exhibe un alto potencial para mejorar la precisión diagnóstica en patologías como el cáncer colorectal, el cáncer gástrico y la enfermedad inflamatoria intestinal, utilizando imágenes endoscópicas e histopatológicas. Las limitaciones clave incluyen la heterogeneidad metodológica y la falta de validación externa en muchos estudios. Conclusiones: La IA es una herramienta prometedora para optimizar el diagnóstico quirúrgico de enfermedades digestivas, ofreciendo mayor precisión y eficiencia. Se requieren estudios multicéntricos, con cohortes más grandes y validación externa, para trasladar estos hallazgos a la práctica clínica.Descargas
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Derechos de autor 2025 Verónica Antonella Vizueta Estrada, Glenda Magali Vaca Coronel
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